Triple

T19095828
Position Surface form Disambiguated ID Type / Status
Subject Gran Santiago E467401 entity
Predicate contains P35 FINISHED
Object Maipú 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: Maipú | Statement: [Gran Santiago, contains, Maipú]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maipú
Context triple: [Gran Santiago, contains, Maipú]
  • A. 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.
  • B. Maipú
    Maipú is a renowned wine-producing region in Argentina’s Mendoza Province, noted for its high-quality Malbec and other varietals.
  • 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 (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_69d8dd05ac4c8190b1967d8f97f3fb2f completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e368f20c8190bd84d2ba320991ac completed April 20, 2026, 8:27 a.m.
Created at: April 10, 2026, 12:04 p.m.