Triple

T9100580
Position Surface form Disambiguated ID Type / Status
Subject Universitet station E218139 entity
Predicate hasRussianName P20560 FINISHED
Object Университет E765649 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: Университет | Statement: [Universitet station, hasRussianName, Университет]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Университет
Context triple: [Universitet station, hasRussianName, Университет]
  • A. Universitate
    Universitate is a central Bucharest metro station located near the University of Bucharest and several major cultural and administrative landmarks.
  • B. Universitas
    Universitas is a Latin term commonly used to denote a university or community of scholars dedicated to higher learning and research.
  • C. Universytet chosen
    Universytet is a central Kharkiv Metro station named for its proximity to major universities and academic institutions in the city.
  • D. Universidad
    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.
  • E. Universitetet
    Universitetet is a railway station in Stockholm, Sweden, serving Stockholm University and located on the Roslagsbanan suburban rail line.
  • 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_69ca83d9844081908e561e367fda6d45 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc9711babc8190a336812dd08d9c73 completed April 1, 2026, 3:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0182d8ea08190b4337a77b47019a5 completed April 3, 2026, 7:42 p.m.
Created at: March 30, 2026, 7:15 p.m.