Triple

T10246869
Position Surface form Disambiguated ID Type / Status
Subject NM-73 E240236 entity
Predicate lineTerminus P46766 FINISHED
Object Universidad E218788 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: Universidad | Statement: [NM-73, lineTerminus, Universidad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Universidad
Context triple: [NM-73, lineTerminus, Universidad]
  • A. Universidad chosen
    Universidad is a Mexico City Metro station that serves as a major southern terminus and gateway to the National Autonomous University of Mexico (UNAM) campus.
  • B. Universitas
    Universitas is a Latin term commonly used to denote a university or community of scholars dedicated to higher learning and research.
  • C. Universitate
    Universitate is a central Bucharest metro station located near the University of Bucharest and several major cultural and administrative landmarks.
  • D. Universytet
    Universytet is a central Kharkiv Metro station named for its proximity to major universities and academic institutions in the city.
  • E. University College
    University College is an academic division of Texas A&M University–Corpus Christi that provides foundational coursework and support services to help students transition into and succeed in their degree programs.
  • 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_69d381a7e198819090280d5ab885d59e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4dfbfa26c8190b536655d33112ddf completed April 7, 2026, 10:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f7a597188190880200d13784f18f completed April 9, 2026, 12:49 a.m.
Created at: April 6, 2026, 11:27 a.m.