Triple

T11679833
Position Surface form Disambiguated ID Type / Status
Subject Pureza station E277585 entity
Predicate hasAdjacentStation P231 FINISHED
Object Legarda station E277584 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: Legarda station | Statement: [Pureza station, hasAdjacentStation, Legarda station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Legarda station
Context triple: [Pureza station, hasAdjacentStation, Legarda station]
  • A. Legarda station chosen
    Legarda station is an elevated rapid transit stop on Manila’s LRT Line 2 serving the Sampaloc area and nearby universities.
  • B. La Estrella station
    La Estrella station is the southern terminal station of Line A of the Medellín Metro system in Colombia.
  • C. Cabitos station
    Cabitos station is a stop on Lima Metro’s Line 1 serving passengers in the southern part of Peru’s capital city.
  • D. Oriente station
    Oriente station is a major multimodal transport hub in Lisbon, Portugal, serving as a key connection point for trains, metro, buses, and regional services.
  • E. Tasqueña station
    Tasqueña station is a major southern transit hub in Mexico City that serves as the terminus for the Tren Ligero light rail and connects with the city’s metro and bus networks.
  • 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_69d6aafd0a448190b44da30af8c6c519 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a461b0908190bef4e1c6777affcf completed April 10, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef14007dd08190b60640be9949ca26 completed April 27, 2026, 7:45 a.m.
Created at: April 8, 2026, 9:40 p.m.