Triple

T239418
Position Surface form Disambiguated ID Type / Status
Subject IANA time zone database E4894 entity
Predicate usedBy P260 FINISHED
Object PostgreSQL E17669 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: PostgreSQL | Statement: [IANA time zone database, usedBy, PostgreSQL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PostgreSQL
Context triple: [IANA time zone database, usedBy, PostgreSQL]
  • A. PostgreSQL chosen
    PostgreSQL is a powerful open-source relational database management system known for its robustness, extensibility, and strong standards compliance.
  • B. Amazon Redshift
    Amazon Redshift is a fully managed, cloud-based data warehousing service from Amazon Web Services designed for fast querying and analysis of large datasets using SQL.
  • C. Oracle Database
    Oracle Database is a widely used enterprise relational database management system known for its scalability, reliability, and robust support for complex data workloads.
  • D. SQL
    SQL (Structured Query Language) is a standardized programming language used to manage, query, and manipulate data in relational database management systems.
  • E. 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.
  • 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_69a257c3d0708190b0871c4269d273e6 completed Feb. 28, 2026, 2:49 a.m.
NER Named-entity recognition batch_69a25ceaecdc81909e9ff49cb6a4e02a completed Feb. 28, 2026, 3:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3695ec8cc8190a070462cd0022f6a completed Feb. 28, 2026, 10:17 p.m.
Created at: Feb. 28, 2026, 2:53 a.m.