Triple

T817013
Position Surface form Disambiguated ID Type / Status
Subject Google BigQuery E17670 entity
Predicate supportsQueryLanguage P203 FINISHED
Object 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: SQL | Statement: [Google BigQuery, supportsQueryLanguage, SQL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SQL
Context triple: [Google BigQuery, supportsQueryLanguage, 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. 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.
  • C. PL/SQL
    PL/SQL is Oracle's proprietary procedural extension to SQL, used for writing stored procedures, functions, and complex database logic within Oracle Database.
  • D. MySQL
    MySQL is a widely used open-source relational database management system known for its reliability, performance, and role in powering many web applications and services.
  • E. SQLite
    SQLite is a lightweight, self-contained, serverless SQL database engine widely embedded in applications, operating systems, and devices.
  • 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_69a4b2b503d48190bd4f33548a22d5fe completed March 1, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7a3b47ba481908a8db2bec414a3e4 completed March 4, 2026, 3:15 a.m.
Created at: March 1, 2026, 7:38 p.m.