Triple

T1668656
Position Surface form Disambiguated ID Type / Status
Subject Data Control Language E36072 entity
Predicate partOf P40 FINISHED
Object Structured Query Language 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: Structured Query Language | Statement: [Data Control Language, partOf, Structured Query Language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Structured Query Language
Context triple: [Data Control Language, partOf, Structured Query Language]
  • 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. Data Control Language
    Data Control Language (DCL) is a subset of SQL used to define and manage access permissions and security controls on database objects.
  • D. 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.
  • E. 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.
  • 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_69a8861286808190939afff3ce8ee31e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90adf3d3c81909233e574e79b82a2 completed March 5, 2026, 4:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad683207b08190a86c266aaece4e98 completed March 8, 2026, 12:14 p.m.
Created at: March 4, 2026, 7:29 p.m.