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What is the difference between the various Person APIs?
See this section for a detailed breakdown of the differences between our Person APIs.Can I get a likelihood score in the Person Search API?
The likelihood score that we return in our Enrichment APIs represents the likelihood of the matching logic given the input parameters, so it wouldn’t be relevant in the Person Search API.Can I use the Person Search API to enrich data?
The Person Search API does not use the input cleaning and matching behavior available in the Person Enrichment API. We don’t do any preprocessing (cleaning) of the inputs to the Person Search API, so you’re almost guaranteed to have a lower match rate. What’s more, Person Search API queries and Person Enrichment API queries are structured differently. When you make a Person Enrichment API request, we have a custom-built query that takes the different input parameters and weights them differently, only returning a match in certain cases while using stack ranking in cases where there are multiple matches (for example, John Smith in San Francisco.)Should I use SQL or Elasticsearch for the Person Search API?
Use Elasticsearch when:- You have complicated boolean queries.
- You want to maximize the control that you have over text-based matching (titles, summaries and so forth.)
- You are comfortable writing Elasticsearch queries.
- You are running simple searches with only a few parameters.
- You’re exclusively using ENUM parameters from our data (location, company, major and so forth.)
- You are comfortable writing SQL queries.
Can I use wildcards in my search query?
Yes, wildcard terms are supported. However, we have a hard limit of 20 wildcards per query. See the relevant sections for more information about the limitations in Elasticsearch and SQL search queries.Why is there a 1MB limit on the API requests and the response body?
The error message that you are receiving has occurred because the query is too large and cURL can’t handle the response. Calling the API with Python should alleviate this issue as Python compresses the extra space within an Elasticsearch query. Additional ways to decrease the query size are to reduce the profile count parameter from100 to 60 for each call and to remove the pretty tag. You can get around this limitation by Using POST Requests.