Triple

T14435578
Position Surface form Disambiguated ID Type / Status
Subject LMN E357950 entity
Predicate identifies P310 FINISHED
Object La Moneda metro station E72158 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: La Moneda metro station | Statement: [LMN, identifies, La Moneda metro station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Moneda metro station
Context triple: [LMN, identifies, La Moneda metro station]
  • A. Santiago Metro La Moneda station chosen
    Santiago Metro La Moneda station is a central underground metro stop in Santiago, Chile, serving Line 1 and providing access to the government district and key civic landmarks.
  • B. Baquedano metro station
    Baquedano metro station is a major interchange station of the Santiago Metro in Chile, serving as a key transit hub near the city center.
  • C. Allende metro station
    Allende metro station is a Mexico City Metro station located in the historic center, serving Line 2 near major cultural landmarks such as the Museo Nacional de Arte.
  • D. Manuel Montt metro station
    Manuel Montt metro station is a Santiago Metro station on Line 1, located in the Providencia district of Santiago, Chile.
  • E. Maipú metro station
    Maipú metro station is a rapid transit station on Santiago, Chile’s Metro network serving the Maipú commune.
  • 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_69d8279402a88190821ffa39ae15bccf completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de9148cf4481909082cc91b2f76218 completed April 14, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd5bd5b1d08190a89e6f004a94b361 completed May 8, 2026, 3:43 a.m.
Created at: April 10, 2026, 1:18 a.m.