Triple

T4832051
Position Surface form Disambiguated ID Type / Status
Subject MediaWiki E107967 entity
Predicate usesDatabase P11852 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: [MediaWiki, usesDatabase, PostgreSQL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PostgreSQL
Context triple: [MediaWiki, usesDatabase, PostgreSQL]
  • A. PostgreSQL chosen
    PostgreSQL is a powerful open-source relational database management system known for its robustness, extensibility, and strong standards compliance.
  • B. PostgreSQL documentation
    PostgreSQL documentation is the official, comprehensive reference and user guide for the PostgreSQL relational database system, covering its features, configuration, and extensions.
  • C. PostGIS
    PostGIS is an open-source spatial database extender that adds robust geographic object support and spatial querying capabilities to PostgreSQL.
  • D. MariaDB
    MariaDB is an open-source relational database management system, forked from MySQL, known for its compatibility, performance, and community-driven development.
  • E. PL/pgSQL
    PL/pgSQL is PostgreSQL’s procedural extension of SQL that allows writing stored functions and triggers with control structures like variables, loops, and conditionals.
  • 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_69bd43fac8188190803f0327190621e4 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6cc924e08190b03a7541c629aff9 completed March 20, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69be4dd4224c8190be7568bb611f81a3 completed March 21, 2026, 7:50 a.m.
Created at: March 20, 2026, 1:24 p.m.