Triple

T1817766
Position Surface form Disambiguated ID Type / Status
Subject IBM i E40472 entity
Predicate supportsLanguage P2177 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: [IBM i, supportsLanguage, SQL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SQL
Context triple: [IBM i, supportsLanguage, 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. DB
    DB is the commonly used abbreviation for Deutsche Bahn, Germany’s national railway company and one of the largest rail operators in Europe.
  • 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. 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.
  • E. 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.
  • 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_69a8864526c081908a3a4d74f689e2c5 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa65f7b84081909005ce36ef1199db completed March 6, 2026, 5:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69adbf6019bc81909266b7f03b282f34 completed March 8, 2026, 6:26 p.m.
Created at: March 4, 2026, 7:32 p.m.