Triple

T20157859
Position Surface form Disambiguated ID Type / Status
Subject Metro de la Ciudad de México E491620 entity
Predicate hasLine P35 FINISHED
Object Línea 3 NE NERFINISHED

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: Línea 3 | Statement: [Metro de la Ciudad de México, hasLine, Línea 3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Línea 3
Context triple: [Metro de la Ciudad de México, hasLine, Línea 3]
  • A. Línea 3 chosen
    Línea 3 is a metro line that forms part of an urban rapid transit network, connecting multiple stations and intersecting with other lines to facilitate passenger transfers.
  • B. Línea 4
    Línea 4 is one of the lines of the Mexico City Metro system, known for its elevated tracks and service through the city’s northern and eastern areas.
  • C. Línea 2
    Línea 2 is a metro line that forms part of an urban rapid transit network and connects with other lines, including Línea 6, at designated interchange stations.
  • D. Line 3
    Line 3 is a major rapid transit route of the Guangzhou Metro system, known for its high passenger volume and key role in connecting central urban areas with the airport and suburban districts.
  • E. Line 3
    Line 3 is a major line of the Saint Petersburg Metro system, serving as one of the city's primary rapid transit routes.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da6265f8f0819080b29c752a574088 completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e667e18a0c8190a2cc2b305da28047 completed April 20, 2026, 5:52 p.m.
Created at: April 11, 2026, 11:34 p.m.