Triple

T3490946
Position Surface form Disambiguated ID Type / Status
Subject Jubany Station E73727 entity
Predicate formerNameOf P65 FINISHED
Object Carlini Station E363465 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: Carlini Station | Statement: [Jubany Station, formerNameOf, Carlini Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carlini Station
Context triple: [Jubany Station, formerNameOf, Carlini Station]
  • A. Carlini Station chosen
    Carlini Station is an Argentine Antarctic research base on King George Island, focused on scientific studies of the polar environment and climate.
  • B. La Cisterna station
    La Cisterna station is a major interchange and southern endpoint of Santiago’s metro network, connecting Line 4A with other lines and local transport services.
  • C. Belen station
    Belen station is a commuter rail station in Belen, New Mexico, serving as a key stop on the New Mexico Rail Runner Express line.
  • D. Milano Cadorna station
    Milano Cadorna station is a major railway and metro hub in central Milan that serves as a key terminus for regional and airport rail services.
  • E. Retiro station
    Retiro station is a major Buenos Aires Underground terminus and transport hub located in the Retiro district of Argentina’s capital.
  • 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_69ad85cca8d4819088494e9f3340fab5 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbbaa720c8190af47b052cc66c225 completed March 8, 2026, 6:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69b37e6511b08190b67c353df53599b5 completed March 13, 2026, 3:03 a.m.
Created at: March 8, 2026, 3:18 p.m.