Home / Documentation / Basic Usage / Cross Index Resolution
Basic Usage Tutorials 📖
This tutorial is part of a series to help you learn and perform the basic functions of zentity. Each tutorial adds a little more sophistication to the prior tutorials, so you can start simple and learn the more advanced features over time.
- Exact Name Matching
- Robust Name Matching
- Multiple Attribute Resolution
- Multiple Resolver Resolution
- Cross Index Resolution ← You are here.
- Scoping Resolution
Cross Index Resolution
Many applications of entity resolution require matching records that are scattered across multiple data sets. One application might be to profile everything known about a customer, patient, or employee across different business systems. Another might be to see if a person or organization is present in one or more blacklists.
This tutorial adds more sophistication to the prior tutorial on multiple resolver resolution. This time you will map multiple combinations of attributes (i.e. "resolvers") to multiple fields of multiple indices.
Let's dive in.
Before you start
You must install Elasticsearch, Kibana, and zentity to complete this tutorial. This tutorial was tested with zentity-1.6.1-elasticsearch-7.10.1.
Quick start
You can use the zentity sandbox which has the required software and data for these tutorials. This will let you skip many of the setup steps.
1. Prepare for the tutorial
1.1 Install the required plugins
Note: Skip this step if you're using the zentity sandbox.
This tutorial uses the phonetic analysis plugin and ICU analysis plugin for Elasticsearch. You will need to stop Elasticsearch, install these plugin, and start Elasticsearch. You can learn more about Elasticsearch plugin management here.
For Linux (in the $ES_HOME
directory of a .tar.gz installation):
sudo bin/elasticsearch-plugin install analysis-phonetic
sudo bin/elasticsearch-plugin install analysis-icu
For Windows (in the $ES_HOME
directory of a .zip installation):
bin/elasticsearch-plugin.bat install analysis-phonetic
bin/elasticsearch-plugin.bat install analysis-icu
1.2 Open the Kibana Console UI
The Kibana Console UI makes it easy to submit requests to Elasticsearch and read responses.
1.3 Delete any old tutorial indices
Note: Skip this step if you're using the zentity sandbox.
Let's start from scratch. Delete any tutorial indices you might have created from other tutorials.
DELETE zentity_tutorial_5_*
1.4 Create the tutorial index
Note: Skip this step if you're using the zentity sandbox.
Now create the indices for this tutorial.
Index A
PUT zentity_tutorial_5_cross_index_resolution_a
{
"settings": {
"index": {
"number_of_shards": 1,
"number_of_replicas": 0,
"analysis" : {
"filter" : {
"street_suffix_map" : {
"pattern" : "(st)",
"type" : "pattern_replace",
"replacement" : "street"
},
"phonetic" : {
"type" : "phonetic",
"encoder" : "nysiis"
},
"punct_white" : {
"pattern" : "\\p{Punct}",
"type" : "pattern_replace",
"replacement" : " "
},
"remove_non_digits" : {
"pattern" : "[^\\d]",
"type" : "pattern_replace",
"replacement" : ""
}
},
"analyzer" : {
"name_clean" : {
"filter" : [
"icu_normalizer",
"icu_folding",
"punct_white"
],
"tokenizer" : "standard"
},
"name_phonetic" : {
"filter" : [
"icu_normalizer",
"icu_folding",
"punct_white",
"phonetic"
],
"tokenizer" : "standard"
},
"street_clean" : {
"filter" : [
"icu_normalizer",
"icu_folding",
"punct_white",
"trim"
],
"tokenizer" : "keyword"
},
"phone_clean" : {
"filter" : [
"remove_non_digits"
],
"tokenizer" : "keyword"
}
}
}
}
},
"mappings": {
"properties": {
"id_a": {
"type": "keyword"
},
"first_name_a": {
"type": "text",
"fields": {
"clean": {
"type": "text",
"analyzer": "name_clean"
},
"phonetic": {
"type": "text",
"analyzer": "name_phonetic"
}
}
},
"last_name_a": {
"type": "text",
"fields": {
"clean": {
"type": "text",
"analyzer": "name_clean"
},
"phonetic": {
"type": "text",
"analyzer": "name_phonetic"
}
}
},
"street_a": {
"type": "text",
"fields": {
"clean": {
"type": "text",
"analyzer": "street_clean"
}
}
},
"city_a": {
"type": "text",
"fields": {
"clean": {
"type": "text",
"analyzer": "name_clean"
}
}
},
"state_a": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword"
}
}
},
"phone_a": {
"type": "text",
"fields": {
"clean": {
"type": "text",
"analyzer": "phone_clean"
}
}
},
"email_a": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword"
}
}
}
}
}
}
Index B
PUT zentity_tutorial_5_cross_index_resolution_b
{
"settings": {
"index": {
"number_of_shards": 1,
"number_of_replicas": 0,
"analysis" : {
"filter" : {
"street_suffix_map" : {
"pattern" : "(st)",
"type" : "pattern_replace",
"replacement" : "street"
},
"phonetic" : {
"type" : "phonetic",
"encoder" : "nysiis"
},
"punct_white" : {
"pattern" : "\\p{Punct}",
"type" : "pattern_replace",
"replacement" : " "
},
"remove_non_digits" : {
"pattern" : "[^\\d]",
"type" : "pattern_replace",
"replacement" : ""
}
},
"analyzer" : {
"name_clean" : {
"filter" : [
"icu_normalizer",
"icu_folding",
"punct_white"
],
"tokenizer" : "standard"
},
"name_phonetic" : {
"filter" : [
"icu_normalizer",
"icu_folding",
"punct_white",
"phonetic"
],
"tokenizer" : "standard"
},
"street_clean" : {
"filter" : [
"icu_normalizer",
"icu_folding",
"punct_white",
"trim"
],
"tokenizer" : "keyword"
},
"phone_clean" : {
"filter" : [
"remove_non_digits"
],
"tokenizer" : "keyword"
}
}
}
}
},
"mappings": {
"properties": {
"id_b": {
"type": "keyword"
},
"first_name_b": {
"type": "text",
"fields": {
"clean": {
"type": "text",
"analyzer": "name_clean"
},
"phonetic": {
"type": "text",
"analyzer": "name_phonetic"
}
}
},
"last_name_b": {
"type": "text",
"fields": {
"clean": {
"type": "text",
"analyzer": "name_clean"
},
"phonetic": {
"type": "text",
"analyzer": "name_phonetic"
}
}
},
"street_b": {
"type": "text",
"fields": {
"clean": {
"type": "text",
"analyzer": "street_clean"
}
}
},
"city_b": {
"type": "text",
"fields": {
"clean": {
"type": "text",
"analyzer": "name_clean"
}
}
},
"state_b": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword"
}
}
},
"phone_b": {
"type": "text",
"fields": {
"clean": {
"type": "text",
"analyzer": "phone_clean"
}
}
},
"email_b": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword"
}
}
}
}
}
}
1.5 Load the tutorial data
Note: Skip this step if you're using the zentity sandbox.
Add the tutorial data to the index.
POST _bulk?refresh
{"index": {"_id": "1", "_index": "zentity_tutorial_5_cross_index_resolution_a"}}
{"city_a": "Washington", "email_a": "[email protected]", "first_name_a": "Allie", "id_a": "1", "last_name_a": "Jones", "phone_a": "202-555-1234", "state_a": "DC", "street_a": "123 Main St"}
{"index": {"_id": "2", "_index": "zentity_tutorial_5_cross_index_resolution_b"}}
{"city_b": "Washington", "email_b": "", "first_name_b": "Alicia", "id_b": "2", "last_name_b": "Johnson", "phone_b": "202-123-4567", "state_b": "DC", "street_b": "300 Main St"}
{"index": {"_id": "3", "_index": "zentity_tutorial_5_cross_index_resolution_a"}}
{"city_a": "Washington", "email_a": "", "first_name_a": "Allie", "id_a": "3", "last_name_a": "Jones", "phone_a": "", "state_a": "DC", "street_a": "123 Main St"}
{"index": {"_id": "4", "_index": "zentity_tutorial_5_cross_index_resolution_b"}}
{"city_b": "", "email_b": "", "first_name_b": "Ally", "id_b": "4", "last_name_b": "Joans", "phone_b": "202-555-1234", "state_b": "", "street_b": ""}
{"index": {"_id": "5", "_index": "zentity_tutorial_5_cross_index_resolution_a"}}
{"city_a": "Arlington", "email_a": "[email protected]", "first_name_a": "Eli", "id_a": "5", "last_name_a": "Jonas", "phone_a": "", "state_a": "VA", "street_a": "500 23rd Street"}
{"index": {"_id": "6", "_index": "zentity_tutorial_5_cross_index_resolution_b"}}
{"city_b": "Washington", "email_b": "[email protected]", "first_name_b": "Allison", "id_b": "6", "last_name_b": "Jones", "phone_b": "202-555-1234", "state_b": "DC", "street_b": "123 Main St"}
{"index": {"_id": "7", "_index": "zentity_tutorial_5_cross_index_resolution_a"}}
{"city_a": "Washington", "email_a": "", "first_name_a": "Allison", "id_a": "7", "last_name_a": "Smith", "phone_a": "+1 (202) 555 1234", "state_a": "DC", "street_a": "555 Broad St"}
{"index": {"_id": "8", "_index": "zentity_tutorial_5_cross_index_resolution_b"}}
{"city_b": "Washington", "email_b": "[email protected]", "first_name_b": "Alan", "id_b": "8", "last_name_b": "Smith", "phone_b": "202-000-5555", "state_b": "DC", "street_b": "555 Broad St"}
{"index": {"_id": "9", "_index": "zentity_tutorial_5_cross_index_resolution_a"}}
{"city_a": "Washington", "email_a": "[email protected]", "first_name_a": "Alan", "id_a": "9", "last_name_a": "Smith", "phone_a": "2020005555", "state_a": "DC", "street_a": "555 Broad St"}
{"index": {"_id": "10", "_index": "zentity_tutorial_5_cross_index_resolution_b"}}
{"city_b": "Washington", "email_b": "", "first_name_b": "Alison", "id_b": "10", "last_name_b": "Smith", "phone_b": "202-555-9876", "state_b": "DC", "street_b": "555 Broad St"}
{"index": {"_id": "11", "_index": "zentity_tutorial_5_cross_index_resolution_a"}}
{"city_a": "", "email_a": "[email protected]", "first_name_a": "Alison", "id_a": "11", "last_name_a": "Jones-Smith", "phone_a": "2025559867", "state_a": "", "street_a": ""}
{"index": {"_id": "12", "_index": "zentity_tutorial_5_cross_index_resolution_b"}}
{"city_b": "Washington", "email_b": "[email protected]", "first_name_b": "Allison", "id_b": "12", "last_name_b": "Jones-Smith", "phone_b": "", "state_b": "DC", "street_b": "555 Broad St"}
{"index": {"_id": "13", "_index": "zentity_tutorial_5_cross_index_resolution_a"}}
{"city_a": "Arlington", "email_a": "[email protected]", "first_name_a": "Allison", "id_a": "13", "last_name_a": "Jones Smith", "phone_a": "703-555-5555", "state_a": "VA", "street_a": "1 Corporate Way"}
{"index": {"_id": "14", "_index": "zentity_tutorial_5_cross_index_resolution_b"}}
{"city_b": "Arlington", "email_b": "[email protected]", "first_name_b": "Elise", "id_b": "14", "last_name_b": "Jonas", "phone_b": "703-555-5555", "state_b": "VA", "street_b": "1 Corporate Way"}
Here's what the tutorial data looks like.
Index A
id_a | first_name_a | last_name_a | street_a | city_a | state_a | phone_a | email_a |
---|---|---|---|---|---|---|---|
1 | Allie | Jones | 123 Main St | Washington | DC | 202-555-1234 | [email protected] |
3 | Allie | Jones | 123 Main St | Washington | DC | ||
5 | Eli | Jonas | 500 23rd Street | Arlington | VA | [email protected] | |
7 | Allison | Smith | 555 Broad St | Washington | DC | +1 (202) 555 1234 | |
9 | Alan | Smith | 555 Broad St | Washington | DC | 2020005555 | [email protected] |
11 | Alison | Jones-Smith | 2025559867 | [email protected] | |||
13 | Allison | Jones Smith | 1 Corporate Way | Arlington | VA | 703-555-5555 | [email protected] |
Index B
id_b | first_name_b | last_name_b | street_b | city_b | state_b | phone_b | email_b |
---|---|---|---|---|---|---|---|
2 | Alicia | Johnson | 300 Main St | Washington | DC | 202-123-4567 | |
4 | Ally | Joans | 202-555-1234 | ||||
6 | Allison | Jones | 123 Main St | Washington | DC | 202-555-1234 | [email protected] |
8 | Alan | Smith | 555 Broad St | Washington | DC | 202-000-5555 | [email protected] |
10 | Alison | Smith | 555 Broad St | Washington | DC | 202-555-9876 | |
12 | Allison | Jones-Smith | 555 Broad St | Washington | DC | [email protected] | |
14 | Elise | Jonas | 1 Corporate Way | Arlington | VA | 703-555-5555 | [email protected] |
2. Create the entity model
Note: Skip this step if you're using the zentity sandbox.
Let's use the Models API to create the entity model below. We'll review each part of the model in depth.
Request
PUT _zentity/models/zentity_tutorial_5_person
{
"attributes": {
"first_name": {
"type": "string"
},
"last_name": {
"type": "string"
},
"street": {
"type": "string"
},
"city": {
"type": "string"
},
"state": {
"type": "string"
},
"phone": {
"type": "string"
},
"email": {
"type": "string"
}
},
"resolvers": {
"name_street_city_state": {
"attributes": [ "first_name", "last_name", "street", "city", "state" ]
},
"name_phone": {
"attributes": [ "first_name", "last_name", "phone" ]
},
"name_email": {
"attributes": [ "first_name", "last_name", "email" ]
},
"email_phone": {
"attributes": [ "email", "phone" ]
}
},
"matchers": {
"simple": {
"clause": {
"match": {
"{{ field }}": "{{ value }}"
}
}
},
"fuzzy": {
"clause": {
"match": {
"{{ field }}": {
"query": "{{ value }}",
"fuzziness": "1"
}
}
}
},
"exact": {
"clause": {
"term": {
"{{ field }}": "{{ value }}"
}
}
}
},
"indices": {
"zentity_tutorial_5_cross_index_resolution_a": {
"fields": {
"first_name_a.clean": {
"attribute": "first_name",
"matcher": "fuzzy"
},
"first_name_a.phonetic": {
"attribute": "first_name",
"matcher": "simple"
},
"last_name_a.clean": {
"attribute": "last_name",
"matcher": "fuzzy"
},
"last_name_a.phonetic": {
"attribute": "last_name",
"matcher": "simple"
},
"street_a.clean": {
"attribute": "street",
"matcher": "fuzzy"
},
"city_a.clean": {
"attribute": "city",
"matcher": "fuzzy"
},
"state_a.keyword": {
"attribute": "state",
"matcher": "exact"
},
"phone_a.clean": {
"attribute": "phone",
"matcher": "fuzzy"
},
"email_a.keyword": {
"attribute": "email",
"matcher": "exact"
}
}
},
"zentity_tutorial_5_cross_index_resolution_b": {
"fields": {
"first_name_b.clean": {
"attribute": "first_name",
"matcher": "fuzzy"
},
"first_name_b.phonetic": {
"attribute": "first_name",
"matcher": "simple"
},
"last_name_b.clean": {
"attribute": "last_name",
"matcher": "fuzzy"
},
"last_name_b.phonetic": {
"attribute": "last_name",
"matcher": "simple"
},
"street_b.clean": {
"attribute": "street",
"matcher": "fuzzy"
},
"city_b.clean": {
"attribute": "city",
"matcher": "fuzzy"
},
"state_b.keyword": {
"attribute": "state",
"matcher": "exact"
},
"phone_b.clean": {
"attribute": "phone",
"matcher": "fuzzy"
},
"email_b.keyword": {
"attribute": "email",
"matcher": "exact"
}
}
}
}
}
2.1 Review the attributes
We defined five attributes as shown in this section:
{
"attributes": {
"first_name": {
"type": "string"
},
"last_name": {
"type": "string"
},
"street": {
"type": "string"
},
"city": {
"type": "string"
},
"state": {
"type": "string"
},
"phone": {
"type": "string"
},
"email": {
"type": "string"
}
}
}
2.2 Review the resolvers
We defined four resolvers as shown in this section:
{
"resolvers": {
"name_street_city_state": {
"attributes": [ "first_name", "last_name", "street", "city", "state" ]
},
"name_phone": {
"attributes": [ "first_name", "last_name", "phone" ]
},
"name_email": {
"attributes": [ "first_name", "last_name", "email" ]
},
"email_phone": {
"attributes": [ "email", "phone" ]
}
}
}
2.3 Review the matchers
We defined three matchers called "simple"
, "fuzzy"
, and "exact"
as shown
in this section:
{
"matchers": {
"simple": {
"clause": {
"match": {
"{{ field }}": "{{ value }}"
}
}
},
"fuzzy": {
"clause": {
"match": {
"{{ field }}": {
"query": "{{ value }}",
"fuzziness": "1"
}
}
}
},
"exact": {
"clause": {
"term": {
"{{ field }}": "{{ value }}"
}
}
}
}
}
2.4 Review the indices
We defined a two indices as shown in this section:
{
"indices": {
"zentity_tutorial_5_cross_index_resolution_a": {
"fields": {
"first_name_a.clean": {
"attribute": "first_name",
"matcher": "fuzzy"
},
"first_name_a.phonetic": {
"attribute": "first_name",
"matcher": "simple"
},
"last_name_a.clean": {
"attribute": "last_name",
"matcher": "fuzzy"
},
"last_name_a.phonetic": {
"attribute": "last_name",
"matcher": "simple"
},
"street_a.clean": {
"attribute": "street",
"matcher": "fuzzy"
},
"city_a.clean": {
"attribute": "city",
"matcher": "fuzzy"
},
"state_a.keyword": {
"attribute": "state",
"matcher": "exact"
},
"phone_a.clean": {
"attribute": "phone",
"matcher": "fuzzy"
},
"email_a.keyword": {
"attribute": "email",
"matcher": "exact"
}
}
},
"zentity_tutorial_5_cross_index_resolution_b": {
"fields": {
"first_name_b.clean": {
"attribute": "first_name",
"matcher": "fuzzy"
},
"first_name_b.phonetic": {
"attribute": "first_name",
"matcher": "simple"
},
"last_name_b.clean": {
"attribute": "last_name",
"matcher": "fuzzy"
},
"last_name_b.phonetic": {
"attribute": "last_name",
"matcher": "simple"
},
"street_b.clean": {
"attribute": "street",
"matcher": "fuzzy"
},
"city_b.clean": {
"attribute": "city",
"matcher": "fuzzy"
},
"state_b.keyword": {
"attribute": "state",
"matcher": "exact"
},
"phone_b.clean": {
"attribute": "phone",
"matcher": "fuzzy"
},
"email_b.keyword": {
"attribute": "email",
"matcher": "exact"
}
}
}
}
}
3. Resolve an entity
3.1 Run a basic resolution job
Let's use the Resolution API to resolve a person with a known first name, last name, and phone number.
Request
POST _zentity/resolution/zentity_tutorial_5_person?pretty&_source=false
{
"attributes": {
"first_name": [ "Allie" ],
"last_name": [ "Jones" ],
"phone": [ "202-555-1234" ]
}
}
Response
{
"took" : 64,
"hits" : {
"total" : 9,
"hits" : [ {
"_index" : "zentity_tutorial_5_cross_index_resolution_a",
"_id" : "1",
"_hop" : 0,
"_query" : 0,
"_attributes" : {
"city" : [ "Washington" ],
"email" : [ "[email protected]" ],
"first_name" : [ "Allie" ],
"last_name" : [ "Jones" ],
"phone" : [ "202-555-1234" ],
"state" : [ "DC" ],
"street" : [ "123 Main St" ]
}
}, {
"_index" : "zentity_tutorial_5_cross_index_resolution_b",
"_id" : "4",
"_hop" : 0,
"_query" : 1,
"_attributes" : {
"city" : [ "" ],
"email" : [ "" ],
"first_name" : [ "Ally" ],
"last_name" : [ "Joans" ],
"phone" : [ "202-555-1234" ],
"state" : [ "" ],
"street" : [ "" ]
}
}, {
"_index" : "zentity_tutorial_5_cross_index_resolution_a",
"_id" : "3",
"_hop" : 1,
"_query" : 0,
"_attributes" : {
"city" : [ "Washington" ],
"email" : [ "" ],
"first_name" : [ "Allie" ],
"last_name" : [ "Jones" ],
"phone" : [ "" ],
"state" : [ "DC" ],
"street" : [ "123 Main St" ]
}
}, {
"_index" : "zentity_tutorial_5_cross_index_resolution_b",
"_id" : "6",
"_hop" : 1,
"_query" : 1,
"_attributes" : {
"city" : [ "Washington" ],
"email" : [ "[email protected]" ],
"first_name" : [ "Allison" ],
"last_name" : [ "Jones" ],
"phone" : [ "202-555-1234" ],
"state" : [ "DC" ],
"street" : [ "123 Main St" ]
}
}, {
"_index" : "zentity_tutorial_5_cross_index_resolution_a",
"_id" : "11",
"_hop" : 2,
"_query" : 0,
"_attributes" : {
"city" : [ "" ],
"email" : [ "[email protected]" ],
"first_name" : [ "Alison" ],
"last_name" : [ "Jones-Smith" ],
"phone" : [ "2025559867" ],
"state" : [ "" ],
"street" : [ "" ]
}
}, {
"_index" : "zentity_tutorial_5_cross_index_resolution_a",
"_id" : "7",
"_hop" : 3,
"_query" : 0,
"_attributes" : {
"city" : [ "Washington" ],
"email" : [ "" ],
"first_name" : [ "Allison" ],
"last_name" : [ "Smith" ],
"phone" : [ "+1 (202) 555 1234" ],
"state" : [ "DC" ],
"street" : [ "555 Broad St" ]
}
}, {
"_index" : "zentity_tutorial_5_cross_index_resolution_b",
"_id" : "10",
"_hop" : 3,
"_query" : 1,
"_attributes" : {
"city" : [ "Washington" ],
"email" : [ "" ],
"first_name" : [ "Alison" ],
"last_name" : [ "Smith" ],
"phone" : [ "202-555-9876" ],
"state" : [ "DC" ],
"street" : [ "555 Broad St" ]
}
}, {
"_index" : "zentity_tutorial_5_cross_index_resolution_b",
"_id" : "12",
"_hop" : 4,
"_query" : 1,
"_attributes" : {
"city" : [ "Washington" ],
"email" : [ "[email protected]" ],
"first_name" : [ "Allison" ],
"last_name" : [ "Jones-Smith" ],
"phone" : [ "" ],
"state" : [ "DC" ],
"street" : [ "555 Broad St" ]
}
}, {
"_index" : "zentity_tutorial_5_cross_index_resolution_a",
"_id" : "13",
"_hop" : 5,
"_query" : 0,
"_attributes" : {
"city" : [ "Arlington" ],
"email" : [ "[email protected]" ],
"first_name" : [ "Allison" ],
"last_name" : [ "Jones Smith" ],
"phone" : [ "703-555-5555" ],
"state" : [ "VA" ],
"street" : [ "1 Corporate Way" ]
}
} ]
}
}
As expected, we retrieved the same results as the prior tutorial on
multiple resolver resolution
even though the documents were separated into two indices. These are shown in
the "_index"
, "_hop"
, and "_query"
fields.
3.2 Show the "_source"
We can include the original values of each document as they exist in Elasticsearch.
Let's run the job again, and now let's include the "_source"
field of each document. The "_source"
field is the original JSON document that's stored in an Elasticsearch index.
Request
POST _zentity/resolution/zentity_tutorial_5_person?pretty&_source=true
{
"attributes": {
"first_name": [ "Allie" ],
"last_name": [ "Jones" ],
"phone": [ "202-555-1234" ]
}
}
Response
{
"took" : 62,
"hits" : {
"total" : 9,
"hits" : [ {
"_index" : "zentity_tutorial_5_cross_index_resolution_a",
"_id" : "1",
"_hop" : 0,
"_query" : 0,
"_attributes" : {
"city" : [ "Washington" ],
"email" : [ "[email protected]" ],
"first_name" : [ "Allie" ],
"last_name" : [ "Jones" ],
"phone" : [ "202-555-1234" ],
"state" : [ "DC" ],
"street" : [ "123 Main St" ]
},
"_source" : {
"city_a" : "Washington",
"email_a" : "[email protected]",
"first_name_a" : "Allie",
"id_a" : "1",
"last_name_a" : "Jones",
"phone_a" : "202-555-1234",
"state_a" : "DC",
"street_a" : "123 Main St"
}
}, {
"_index" : "zentity_tutorial_5_cross_index_resolution_b",
"_id" : "4",
"_hop" : 0,
"_query" : 1,
"_attributes" : {
"city" : [ "" ],
"email" : [ "" ],
"first_name" : [ "Ally" ],
"last_name" : [ "Joans" ],
"phone" : [ "202-555-1234" ],
"state" : [ "" ],
"street" : [ "" ]
},
"_source" : {
"city_b" : "",
"email_b" : "",
"first_name_b" : "Ally",
"id_b" : "4",
"last_name_b" : "Joans",
"phone_b" : "202-555-1234",
"state_b" : "",
"street_b" : ""
}
}, {
"_index" : "zentity_tutorial_5_cross_index_resolution_a",
"_id" : "3",
"_hop" : 1,
"_query" : 0,
"_attributes" : {
"city" : [ "Washington" ],
"email" : [ "" ],
"first_name" : [ "Allie" ],
"last_name" : [ "Jones" ],
"phone" : [ "" ],
"state" : [ "DC" ],
"street" : [ "123 Main St" ]
},
"_source" : {
"city_a" : "Washington",
"email_a" : "",
"first_name_a" : "Allie",
"id_a" : "3",
"last_name_a" : "Jones",
"phone_a" : "",
"state_a" : "DC",
"street_a" : "123 Main St"
}
}, {
"_index" : "zentity_tutorial_5_cross_index_resolution_b",
"_id" : "6",
"_hop" : 1,
"_query" : 1,
"_attributes" : {
"city" : [ "Washington" ],
"email" : [ "[email protected]" ],
"first_name" : [ "Allison" ],
"last_name" : [ "Jones" ],
"phone" : [ "202-555-1234" ],
"state" : [ "DC" ],
"street" : [ "123 Main St" ]
},
"_source" : {
"city_b" : "Washington",
"email_b" : "[email protected]",
"first_name_b" : "Allison",
"id_b" : "6",
"last_name_b" : "Jones",
"phone_b" : "202-555-1234",
"state_b" : "DC",
"street_b" : "123 Main St"
}
}, {
"_index" : "zentity_tutorial_5_cross_index_resolution_a",
"_id" : "11",
"_hop" : 2,
"_query" : 0,
"_attributes" : {
"city" : [ "" ],
"email" : [ "[email protected]" ],
"first_name" : [ "Alison" ],
"last_name" : [ "Jones-Smith" ],
"phone" : [ "2025559867" ],
"state" : [ "" ],
"street" : [ "" ]
},
"_source" : {
"city_a" : "",
"email_a" : "[email protected]",
"first_name_a" : "Alison",
"id_a" : "11",
"last_name_a" : "Jones-Smith",
"phone_a" : "2025559867",
"state_a" : "",
"street_a" : ""
}
}, {
"_index" : "zentity_tutorial_5_cross_index_resolution_a",
"_id" : "7",
"_hop" : 3,
"_query" : 0,
"_attributes" : {
"city" : [ "Washington" ],
"email" : [ "" ],
"first_name" : [ "Allison" ],
"last_name" : [ "Smith" ],
"phone" : [ "+1 (202) 555 1234" ],
"state" : [ "DC" ],
"street" : [ "555 Broad St" ]
},
"_source" : {
"city_a" : "Washington",
"email_a" : "",
"first_name_a" : "Allison",
"id_a" : "7",
"last_name_a" : "Smith",
"phone_a" : "+1 (202) 555 1234",
"state_a" : "DC",
"street_a" : "555 Broad St"
}
}, {
"_index" : "zentity_tutorial_5_cross_index_resolution_b",
"_id" : "10",
"_hop" : 3,
"_query" : 1,
"_attributes" : {
"city" : [ "Washington" ],
"email" : [ "" ],
"first_name" : [ "Alison" ],
"last_name" : [ "Smith" ],
"phone" : [ "202-555-9876" ],
"state" : [ "DC" ],
"street" : [ "555 Broad St" ]
},
"_source" : {
"city_b" : "Washington",
"email_b" : "",
"first_name_b" : "Alison",
"id_b" : "10",
"last_name_b" : "Smith",
"phone_b" : "202-555-9876",
"state_b" : "DC",
"street_b" : "555 Broad St"
}
}, {
"_index" : "zentity_tutorial_5_cross_index_resolution_b",
"_id" : "12",
"_hop" : 4,
"_query" : 1,
"_attributes" : {
"city" : [ "Washington" ],
"email" : [ "[email protected]" ],
"first_name" : [ "Allison" ],
"last_name" : [ "Jones-Smith" ],
"phone" : [ "" ],
"state" : [ "DC" ],
"street" : [ "555 Broad St" ]
},
"_source" : {
"city_b" : "Washington",
"email_b" : "[email protected]",
"first_name_b" : "Allison",
"id_b" : "12",
"last_name_b" : "Jones-Smith",
"phone_b" : "",
"state_b" : "DC",
"street_b" : "555 Broad St"
}
}, {
"_index" : "zentity_tutorial_5_cross_index_resolution_a",
"_id" : "13",
"_hop" : 5,
"_query" : 0,
"_attributes" : {
"city" : [ "Arlington" ],
"email" : [ "[email protected]" ],
"first_name" : [ "Allison" ],
"last_name" : [ "Jones Smith" ],
"phone" : [ "703-555-5555" ],
"state" : [ "VA" ],
"street" : [ "1 Corporate Way" ]
},
"_source" : {
"city_a" : "Arlington",
"email_a" : "[email protected]",
"first_name_a" : "Allison",
"id_a" : "13",
"last_name_a" : "Jones Smith",
"phone_a" : "703-555-5555",
"state_a" : "VA",
"street_a" : "1 Corporate Way"
}
} ]
}
}
Notice how the "_attributes"
of each result have the same field names
regardless of which index the documents came from. The "_source"
fields show
the original names of the fields as they exist in the indices. This mapping of
the source field names to the canonical attribute names allows you to access
their under as a common schema. This makes it much easier to analyze the values
of the entity.
3.3 Show the "_explanation"
We can learn how the documents matched, too.
Let's run the job again, and now let's include the "_explanation"
field to see exactly why each document matched. The "_explanation"
field tells
us which resolvers caused a document to match, and more specifically, which
input value matched which indexed value using which matcher and any parameters.
Request
POST _zentity/resolution/zentity_tutorial_5_person?pretty&_source=true&_explanation=true
{
"attributes": {
"first_name": [ "Allie" ],
"last_name": [ "Jones" ],
"phone": [ "202-555-1234" ]
}
}
Response
{
"took" : 77,
"hits" : {
"total" : 9,
"hits" : [ {
"_index" : "zentity_tutorial_5_cross_index_resolution_a",
"_id" : "1",
"_hop" : 0,
"_query" : 0,
"_attributes" : {
"city" : [ "Washington" ],
"email" : [ "[email protected]" ],
"first_name" : [ "Allie" ],
"last_name" : [ "Jones" ],
"phone" : [ "202-555-1234" ],
"state" : [ "DC" ],
"street" : [ "123 Main St" ]
},
"_explanation" : {
"resolvers" : {
"name_phone" : {
"attributes" : [ "first_name", "last_name", "phone" ]
}
},
"matches" : [ {
"attribute" : "first_name",
"target_field" : "first_name_a.clean",
"target_value" : "Allie",
"input_value" : "Allie",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "first_name",
"target_field" : "first_name_a.phonetic",
"target_value" : "Allie",
"input_value" : "Allie",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_a.clean",
"target_value" : "Jones",
"input_value" : "Jones",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_a.phonetic",
"target_value" : "Jones",
"input_value" : "Jones",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "phone",
"target_field" : "phone_a.clean",
"target_value" : "202-555-1234",
"input_value" : "202-555-1234",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
} ]
},
"_source" : {
"city_a" : "Washington",
"email_a" : "[email protected]",
"first_name_a" : "Allie",
"id_a" : "1",
"last_name_a" : "Jones",
"phone_a" : "202-555-1234",
"state_a" : "DC",
"street_a" : "123 Main St"
}
}, {
"_index" : "zentity_tutorial_5_cross_index_resolution_b",
"_id" : "4",
"_hop" : 0,
"_query" : 1,
"_attributes" : {
"city" : [ "" ],
"email" : [ "" ],
"first_name" : [ "Ally" ],
"last_name" : [ "Joans" ],
"phone" : [ "202-555-1234" ],
"state" : [ "" ],
"street" : [ "" ]
},
"_explanation" : {
"resolvers" : {
"name_phone" : {
"attributes" : [ "first_name", "last_name", "phone" ]
}
},
"matches" : [ {
"attribute" : "first_name",
"target_field" : "first_name_b.phonetic",
"target_value" : "Ally",
"input_value" : "Allie",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_b.phonetic",
"target_value" : "Joans",
"input_value" : "Jones",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "phone",
"target_field" : "phone_b.clean",
"target_value" : "202-555-1234",
"input_value" : "202-555-1234",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
} ]
},
"_source" : {
"city_b" : "",
"email_b" : "",
"first_name_b" : "Ally",
"id_b" : "4",
"last_name_b" : "Joans",
"phone_b" : "202-555-1234",
"state_b" : "",
"street_b" : ""
}
}, {
"_index" : "zentity_tutorial_5_cross_index_resolution_a",
"_id" : "3",
"_hop" : 1,
"_query" : 0,
"_attributes" : {
"city" : [ "Washington" ],
"email" : [ "" ],
"first_name" : [ "Allie" ],
"last_name" : [ "Jones" ],
"phone" : [ "" ],
"state" : [ "DC" ],
"street" : [ "123 Main St" ]
},
"_explanation" : {
"resolvers" : {
"name_street_city_state" : {
"attributes" : [ "city", "first_name", "last_name", "state", "street" ]
}
},
"matches" : [ {
"attribute" : "city",
"target_field" : "city_a.clean",
"target_value" : "Washington",
"input_value" : "Washington",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "first_name",
"target_field" : "first_name_a.clean",
"target_value" : "Allie",
"input_value" : "Allie",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "first_name",
"target_field" : "first_name_a.phonetic",
"target_value" : "Allie",
"input_value" : "Allie",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "first_name",
"target_field" : "first_name_a.phonetic",
"target_value" : "Allie",
"input_value" : "Ally",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_a.clean",
"target_value" : "Jones",
"input_value" : "Jones",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_a.phonetic",
"target_value" : "Jones",
"input_value" : "Joans",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_a.phonetic",
"target_value" : "Jones",
"input_value" : "Jones",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "state",
"target_field" : "state_a.keyword",
"target_value" : "DC",
"input_value" : "DC",
"input_matcher" : "exact",
"input_matcher_params" : { }
}, {
"attribute" : "street",
"target_field" : "street_a.clean",
"target_value" : "123 Main St",
"input_value" : "123 Main St",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
} ]
},
"_source" : {
"city_a" : "Washington",
"email_a" : "",
"first_name_a" : "Allie",
"id_a" : "3",
"last_name_a" : "Jones",
"phone_a" : "",
"state_a" : "DC",
"street_a" : "123 Main St"
}
}, {
"_index" : "zentity_tutorial_5_cross_index_resolution_b",
"_id" : "6",
"_hop" : 1,
"_query" : 1,
"_attributes" : {
"city" : [ "Washington" ],
"email" : [ "[email protected]" ],
"first_name" : [ "Allison" ],
"last_name" : [ "Jones" ],
"phone" : [ "202-555-1234" ],
"state" : [ "DC" ],
"street" : [ "123 Main St" ]
},
"_explanation" : {
"resolvers" : {
"email_phone" : {
"attributes" : [ "email", "phone" ]
}
},
"matches" : [ {
"attribute" : "city",
"target_field" : "city_b.clean",
"target_value" : "Washington",
"input_value" : "Washington",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "email",
"target_field" : "email_b.keyword",
"target_value" : "[email protected]",
"input_value" : "[email protected]",
"input_matcher" : "exact",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_b.clean",
"target_value" : "Jones",
"input_value" : "Jones",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_b.phonetic",
"target_value" : "Jones",
"input_value" : "Joans",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_b.phonetic",
"target_value" : "Jones",
"input_value" : "Jones",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "phone",
"target_field" : "phone_b.clean",
"target_value" : "202-555-1234",
"input_value" : "202-555-1234",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "state",
"target_field" : "state_b.keyword",
"target_value" : "DC",
"input_value" : "DC",
"input_matcher" : "exact",
"input_matcher_params" : { }
}, {
"attribute" : "street",
"target_field" : "street_b.clean",
"target_value" : "123 Main St",
"input_value" : "123 Main St",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
} ]
},
"_source" : {
"city_b" : "Washington",
"email_b" : "[email protected]",
"first_name_b" : "Allison",
"id_b" : "6",
"last_name_b" : "Jones",
"phone_b" : "202-555-1234",
"state_b" : "DC",
"street_b" : "123 Main St"
}
}, {
"_index" : "zentity_tutorial_5_cross_index_resolution_a",
"_id" : "11",
"_hop" : 2,
"_query" : 0,
"_attributes" : {
"city" : [ "" ],
"email" : [ "[email protected]" ],
"first_name" : [ "Alison" ],
"last_name" : [ "Jones-Smith" ],
"phone" : [ "2025559867" ],
"state" : [ "" ],
"street" : [ "" ]
},
"_explanation" : {
"resolvers" : {
"name_email" : {
"attributes" : [ "email", "first_name", "last_name" ]
}
},
"matches" : [ {
"attribute" : "email",
"target_field" : "email_a.keyword",
"target_value" : "[email protected]",
"input_value" : "[email protected]",
"input_matcher" : "exact",
"input_matcher_params" : { }
}, {
"attribute" : "first_name",
"target_field" : "first_name_a.clean",
"target_value" : "Alison",
"input_value" : "Allison",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "first_name",
"target_field" : "first_name_a.phonetic",
"target_value" : "Alison",
"input_value" : "Allison",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_a.clean",
"target_value" : "Jones-Smith",
"input_value" : "Jones",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_a.phonetic",
"target_value" : "Jones-Smith",
"input_value" : "Joans",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_a.phonetic",
"target_value" : "Jones-Smith",
"input_value" : "Jones",
"input_matcher" : "simple",
"input_matcher_params" : { }
} ]
},
"_source" : {
"city_a" : "",
"email_a" : "[email protected]",
"first_name_a" : "Alison",
"id_a" : "11",
"last_name_a" : "Jones-Smith",
"phone_a" : "2025559867",
"state_a" : "",
"street_a" : ""
}
}, {
"_index" : "zentity_tutorial_5_cross_index_resolution_a",
"_id" : "7",
"_hop" : 3,
"_query" : 0,
"_attributes" : {
"city" : [ "Washington" ],
"email" : [ "" ],
"first_name" : [ "Allison" ],
"last_name" : [ "Smith" ],
"phone" : [ "+1 (202) 555 1234" ],
"state" : [ "DC" ],
"street" : [ "555 Broad St" ]
},
"_explanation" : {
"resolvers" : {
"name_phone" : {
"attributes" : [ "first_name", "last_name", "phone" ]
}
},
"matches" : [ {
"attribute" : "city",
"target_field" : "city_a.clean",
"target_value" : "Washington",
"input_value" : "Washington",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "first_name",
"target_field" : "first_name_a.clean",
"target_value" : "Allison",
"input_value" : "Alison",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "first_name",
"target_field" : "first_name_a.clean",
"target_value" : "Allison",
"input_value" : "Allison",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "first_name",
"target_field" : "first_name_a.phonetic",
"target_value" : "Allison",
"input_value" : "Alison",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "first_name",
"target_field" : "first_name_a.phonetic",
"target_value" : "Allison",
"input_value" : "Allison",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_a.clean",
"target_value" : "Smith",
"input_value" : "Jones-Smith",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_a.phonetic",
"target_value" : "Smith",
"input_value" : "Jones-Smith",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "phone",
"target_field" : "phone_a.clean",
"target_value" : "+1 (202) 555 1234",
"input_value" : "202-555-1234",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "state",
"target_field" : "state_a.keyword",
"target_value" : "DC",
"input_value" : "DC",
"input_matcher" : "exact",
"input_matcher_params" : { }
} ]
},
"_source" : {
"city_a" : "Washington",
"email_a" : "",
"first_name_a" : "Allison",
"id_a" : "7",
"last_name_a" : "Smith",
"phone_a" : "+1 (202) 555 1234",
"state_a" : "DC",
"street_a" : "555 Broad St"
}
}, {
"_index" : "zentity_tutorial_5_cross_index_resolution_b",
"_id" : "10",
"_hop" : 3,
"_query" : 1,
"_attributes" : {
"city" : [ "Washington" ],
"email" : [ "" ],
"first_name" : [ "Alison" ],
"last_name" : [ "Smith" ],
"phone" : [ "202-555-9876" ],
"state" : [ "DC" ],
"street" : [ "555 Broad St" ]
},
"_explanation" : {
"resolvers" : {
"name_phone" : {
"attributes" : [ "first_name", "last_name", "phone" ]
}
},
"matches" : [ {
"attribute" : "city",
"target_field" : "city_b.clean",
"target_value" : "Washington",
"input_value" : "Washington",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "first_name",
"target_field" : "first_name_b.clean",
"target_value" : "Alison",
"input_value" : "Alison",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "first_name",
"target_field" : "first_name_b.clean",
"target_value" : "Alison",
"input_value" : "Allison",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "first_name",
"target_field" : "first_name_b.phonetic",
"target_value" : "Alison",
"input_value" : "Alison",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "first_name",
"target_field" : "first_name_b.phonetic",
"target_value" : "Alison",
"input_value" : "Allison",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_b.clean",
"target_value" : "Smith",
"input_value" : "Jones-Smith",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_b.phonetic",
"target_value" : "Smith",
"input_value" : "Jones-Smith",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "phone",
"target_field" : "phone_b.clean",
"target_value" : "202-555-9876",
"input_value" : "2025559867",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "state",
"target_field" : "state_b.keyword",
"target_value" : "DC",
"input_value" : "DC",
"input_matcher" : "exact",
"input_matcher_params" : { }
} ]
},
"_source" : {
"city_b" : "Washington",
"email_b" : "",
"first_name_b" : "Alison",
"id_b" : "10",
"last_name_b" : "Smith",
"phone_b" : "202-555-9876",
"state_b" : "DC",
"street_b" : "555 Broad St"
}
}, {
"_index" : "zentity_tutorial_5_cross_index_resolution_b",
"_id" : "12",
"_hop" : 4,
"_query" : 1,
"_attributes" : {
"city" : [ "Washington" ],
"email" : [ "[email protected]" ],
"first_name" : [ "Allison" ],
"last_name" : [ "Jones-Smith" ],
"phone" : [ "" ],
"state" : [ "DC" ],
"street" : [ "555 Broad St" ]
},
"_explanation" : {
"resolvers" : {
"name_street_city_state" : {
"attributes" : [ "city", "first_name", "last_name", "state", "street" ]
}
},
"matches" : [ {
"attribute" : "city",
"target_field" : "city_b.clean",
"target_value" : "Washington",
"input_value" : "Washington",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "first_name",
"target_field" : "first_name_b.clean",
"target_value" : "Allison",
"input_value" : "Alison",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "first_name",
"target_field" : "first_name_b.clean",
"target_value" : "Allison",
"input_value" : "Allison",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "first_name",
"target_field" : "first_name_b.phonetic",
"target_value" : "Allison",
"input_value" : "Alison",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "first_name",
"target_field" : "first_name_b.phonetic",
"target_value" : "Allison",
"input_value" : "Allison",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_b.clean",
"target_value" : "Jones-Smith",
"input_value" : "Jones",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_b.clean",
"target_value" : "Jones-Smith",
"input_value" : "Jones-Smith",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_b.clean",
"target_value" : "Jones-Smith",
"input_value" : "Smith",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_b.phonetic",
"target_value" : "Jones-Smith",
"input_value" : "Joans",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_b.phonetic",
"target_value" : "Jones-Smith",
"input_value" : "Jones",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_b.phonetic",
"target_value" : "Jones-Smith",
"input_value" : "Jones-Smith",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_b.phonetic",
"target_value" : "Jones-Smith",
"input_value" : "Smith",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "state",
"target_field" : "state_b.keyword",
"target_value" : "DC",
"input_value" : "DC",
"input_matcher" : "exact",
"input_matcher_params" : { }
}, {
"attribute" : "street",
"target_field" : "street_b.clean",
"target_value" : "555 Broad St",
"input_value" : "555 Broad St",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
} ]
},
"_source" : {
"city_b" : "Washington",
"email_b" : "[email protected]",
"first_name_b" : "Allison",
"id_b" : "12",
"last_name_b" : "Jones-Smith",
"phone_b" : "",
"state_b" : "DC",
"street_b" : "555 Broad St"
}
}, {
"_index" : "zentity_tutorial_5_cross_index_resolution_a",
"_id" : "13",
"_hop" : 5,
"_query" : 0,
"_attributes" : {
"city" : [ "Arlington" ],
"email" : [ "[email protected]" ],
"first_name" : [ "Allison" ],
"last_name" : [ "Jones Smith" ],
"phone" : [ "703-555-5555" ],
"state" : [ "VA" ],
"street" : [ "1 Corporate Way" ]
},
"_explanation" : {
"resolvers" : {
"name_email" : {
"attributes" : [ "email", "first_name", "last_name" ]
}
},
"matches" : [ {
"attribute" : "email",
"target_field" : "email_a.keyword",
"target_value" : "[email protected]",
"input_value" : "[email protected]",
"input_matcher" : "exact",
"input_matcher_params" : { }
}, {
"attribute" : "first_name",
"target_field" : "first_name_a.clean",
"target_value" : "Allison",
"input_value" : "Alison",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "first_name",
"target_field" : "first_name_a.clean",
"target_value" : "Allison",
"input_value" : "Allison",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "first_name",
"target_field" : "first_name_a.phonetic",
"target_value" : "Allison",
"input_value" : "Alison",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "first_name",
"target_field" : "first_name_a.phonetic",
"target_value" : "Allison",
"input_value" : "Allison",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_a.clean",
"target_value" : "Jones Smith",
"input_value" : "Jones",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_a.clean",
"target_value" : "Jones Smith",
"input_value" : "Jones-Smith",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_a.clean",
"target_value" : "Jones Smith",
"input_value" : "Smith",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_a.phonetic",
"target_value" : "Jones Smith",
"input_value" : "Joans",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_a.phonetic",
"target_value" : "Jones Smith",
"input_value" : "Jones",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_a.phonetic",
"target_value" : "Jones Smith",
"input_value" : "Jones-Smith",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "last_name_a.phonetic",
"target_value" : "Jones Smith",
"input_value" : "Smith",
"input_matcher" : "simple",
"input_matcher_params" : { }
} ]
},
"_source" : {
"city_a" : "Arlington",
"email_a" : "[email protected]",
"first_name_a" : "Allison",
"id_a" : "13",
"last_name_a" : "Jones Smith",
"phone_a" : "703-555-5555",
"state_a" : "VA",
"street_a" : "1 Corporate Way"
}
} ]
}
}
Conclusion
Congratulations! You learned how to resolve an entity using multiple combinations of attributes mapped to multiple fields across multiple indices.
The next tutorial will introduce scoping resolution. You will limit the scope of an entity resolution job to specific resolvers and indices to prevent unnecessary searches under particular circumstances.
Continue Reading
‹ | Multiple Resolver Resolution | Scoping Resolution | › |
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