Triple

T6560892
Position Surface form Disambiguated ID Type / Status
Subject Sistema de Tren Eléctrico Urbano E153778 entity
Predicate shortName P43 FINISHED
Object SITEUR E153779 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: SITEUR | Statement: [Sistema de Tren Eléctrico Urbano, shortName, SITEUR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SITEUR
Context triple: [Sistema de Tren Eléctrico Urbano, shortName, SITEUR]
  • A. SITEUR chosen
    SITEUR is the public agency that operates the light rail and related mass transit services in the Guadalajara metropolitan area of Mexico.
  • B. Sito
    Sito is an epithet of the Greek goddess Demeter that emphasizes her role as the provider of grain and sustenance.
  • C. SITE
    SITE is a major industrial estate in Pakistan that hosts a large concentration of manufacturing and commercial enterprises.
  • D. Site 52
    Site 52 is one of the designated jar-bearing locations within Laos’s Plain of Jars archaeological landscape, known for its clusters of ancient megalithic stone vessels.
  • E. Site W
    Site W is a secure U.S. government facility in Washington, D.C., associated with classified national security and intelligence operations.
  • 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_69c6880cb35881909b763eb0125236b9 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ae37a5b0819091692fc5def270b9 completed March 27, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cb90ffd48190996a64d79f516e2c completed March 27, 2026, 6:25 p.m.
Created at: March 27, 2026, 1:52 p.m.