Triple

T20132838
Position Surface form Disambiguated ID Type / Status
Subject Cerro Renca E490939 entity
Predicate municipality P852 FINISHED
Object Renca 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: Renca | Statement: [Cerro Renca, municipality, Renca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Renca
Context triple: [Cerro Renca, municipality, Renca]
  • A. Renca chosen
    Renca is a commune and urban area in the Santiago Metropolitan Region of Chile, known for its residential neighborhoods and proximity to central Santiago.
  • B. Resega
    Resega is the former name of the ice hockey arena in Lugano, Switzerland, now known as Cornèr Arena.
  • C. Anejima
    Anejima is a small, uninhabited Japanese island that forms part of the remote Mukojima subgroup in the Ogasawara (Bonin) Islands chain.
  • D. Rancaekek
    Rancaekek is a suburban district in West Java, Indonesia, known as a growing residential and industrial area on the eastern outskirts of Bandung.
  • E. Hita
    Hita is a historic city in Ōita Prefecture on Japan’s Kyushu island, known for its preserved traditional townscape, riverside setting, and summer festivals.
  • 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_69da62651a0c8190a3e05e95e056a66b completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e66763ee908190af64af31b4ca2377 completed April 20, 2026, 5:50 p.m.
Created at: April 11, 2026, 11:32 p.m.