Triple

T10847639
Position Surface form Disambiguated ID Type / Status
Subject Sagrado Corazón station E256054 entity
Predicate publicTransportSystem P1288 FINISHED
Object Tren Urbano E51431 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: Tren Urbano | Statement: [Sagrado Corazón station, publicTransportSystem, Tren Urbano]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tren Urbano
Context triple: [Sagrado Corazón station, publicTransportSystem, Tren Urbano]
  • A. Tren Urbano chosen
    Tren Urbano is a rapid transit rail system serving the San Juan metropolitan area in Puerto Rico, providing urban mass transportation across key municipalities.
  • B. Mi Tren
    Mi Tren is the electric light rail system serving the Guadalajara metropolitan area in the Mexican state of Jalisco.
  • C. Metros
    Metros is the nickname historically used for the MetroStars, the former Major League Soccer team now known as the New York Red Bulls.
  • D. Buenos Aires Underground
    Buenos Aires Underground is the rapid transit system serving Argentina’s capital, known as the oldest subway network in Latin America and a key component of the city’s public transportation.
  • E. Metropolitano
    Metropolitano is a former operator of the San Martín Line, a railway service in Argentina.
  • 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_69d6aa81a5d08190aa86689061d1ddd2 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d75113bc188190ac78df0c51d95de6 completed April 9, 2026, 7:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69e3a91a3e1c819083ef144e7fd5603f completed April 18, 2026, 3:54 p.m.
Created at: April 8, 2026, 9:20 p.m.