Triple

T15913549
Position Surface form Disambiguated ID Type / Status
Subject Universitate metro station E385907 entity
Predicate serves P98 FINISHED
Object Colțea Hospital E631400 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: Colțea Hospital | Statement: [Universitate metro station, serves, Colțea Hospital]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Colțea Hospital
Context triple: [Universitate metro station, serves, Colțea Hospital]
  • A. Colțea Hospital chosen
    Colțea Hospital is a historic medical institution in central Bucharest, Romania, known as one of the city’s oldest and most prominent hospitals.
  • B. Bârlad Municipal Hospital
    Bârlad Municipal Hospital is a public healthcare institution serving as the main medical center for the city of Bârlad and its surrounding region in Romania.
  • C. Medgidia Municipal Hospital
    Medgidia Municipal Hospital is a public healthcare facility serving the medical needs of residents in the city of Medgidia, Romania and its surrounding area.
  • D. Tonna Hospital
    Tonna Hospital is a healthcare facility serving the community of Tonna in Wales.
  • E. Ružinov Hospital
    Ružinov Hospital is a major healthcare facility located in the Ružinov district of Bratislava, Slovakia, providing a wide range of medical services to the local population.
  • 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_69d86da686e4819097cbf3b1fc2d881d completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e15661046c819097a53de2a3e0443b completed April 16, 2026, 9:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb0592b5c8190a4597644864a6bcb completed May 9, 2026, 10:08 p.m.
Created at: April 10, 2026, 4:52 a.m.