Triple

T817016
Position Surface form Disambiguated ID Type / Status
Subject Google BigQuery E17670 entity
Predicate supports P516 FINISHED
Object ANSI SQL E5275 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: ANSI SQL | Statement: [Google BigQuery, supports, ANSI SQL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ANSI SQL
Context triple: [Google BigQuery, supports, ANSI SQL]
  • A. SQL chosen
    SQL (Structured Query Language) is a standardized programming language used to manage, query, and manipulate data in relational database management systems.
  • B. ANSI
    ANSI is a private non-profit organization that oversees the development and coordination of voluntary consensus standards for products, services, processes, and systems in the United States.
  • C. SQL Server
    SQL Server is Microsoft's enterprise-grade relational database management system used for storing, managing, and analyzing data in a wide range of applications.
  • D. JDBC
    JDBC (Java Database Connectivity) is a Java-based API that enables applications to connect to and interact with relational databases in a standardized way.
  • E. ODBC
    ODBC (Open Database Connectivity) is a standard API that enables applications to access and query data from a wide variety of relational and non-relational database management systems using a common interface.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a4937bcaac8190a322524ac6f45a5a completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4ab621d2c819083f10bff4f66c482 completed March 1, 2026, 9:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69a76d8d1a448190be8494fa2776615a completed March 3, 2026, 11:23 p.m.
Created at: March 1, 2026, 7:38 p.m.