Triple

T12341269
Position Surface form Disambiguated ID Type / Status
Subject Tacuba metro station E294230 entity
Predicate hasMetroLine P17559 FINISHED
Object Line 2 E491621 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: Line 2 | Statement: [Tacuba metro station, hasMetroLine, Line 2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 2
Context triple: [Tacuba metro station, hasMetroLine, Line 2]
  • A. Line 2
    Line 2 is a major route of Mexico City’s Metrobús bus rapid transit system, running along key thoroughfares to connect important residential and commercial areas.
  • B. Line 2
    Line 2 is a planned second rapid transit line of the Turin Metro system in Turin, Italy, intended to expand the city's urban rail network.
  • C. Line 2 chosen
    Line 2 is a major rapid transit route of the STC Metro system, serving key districts along one of the network’s primary corridors.
  • D. Line 2
    Line 2 is a major rapid transit route of the Santo Domingo Metro system in the Dominican Republic, serving key east–west corridors of the capital.
  • E. Line 2
    Line 2 is one of the main lines of the Milan Metro rapid transit system, connecting key districts across the city.
  • 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_69d6ab6ccbec8190b09e2d357aa80064 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f7758dc8190bbc6a9ad00b01dce completed April 10, 2026, 6:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62aaa1d548190be065412aab70385 completed May 2, 2026, 4:47 p.m.
Created at: April 8, 2026, 9:53 p.m.