Triple

T12485325
Position Surface form Disambiguated ID Type / Status
Subject Plaza de Maipú station E298416 entity
Predicate locatedIn P40 FINISHED
Object Maipú E184706 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: Maipú | Statement: [Plaza de Maipú station, locatedIn, Maipú]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maipú
Context triple: [Plaza de Maipú station, locatedIn, Maipú]
  • A. Maipú
    Maipú is a renowned wine-producing region in Argentina’s Mendoza Province, noted for its high-quality Malbec and other varietals.
  • B. Maipú chosen
    Maipú is a populous commune and suburb of Santiago, Chile, known for its residential areas, commercial activity, and historical significance in the Santiago Metropolitan Region.
  • C. Talcahuano
    Talcahuano is a major Chilean port city and naval base known for its shipyards and fishing industry.
  • D. Rancagua
    Rancagua is a major Chilean city known for its mining industry and historical significance in the country’s independence, serving as an important commercial and administrative center south of Santiago.
  • E. Chanco
    Chanco is a coastal town and commune in Chile’s Maule Region, known for its agricultural activities and nearby protected natural areas.
  • 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_69d6ada377208190a36011199a4d8558 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94ddf0b6c8190aff4fe267d8f6efe completed April 10, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67188f6b481909885e35dce5a5b69 completed May 2, 2026, 9:50 p.m.
Created at: April 8, 2026, 9:56 p.m.