Triple

T12394926
Position Surface form Disambiguated ID Type / Status
Subject Quinta Normal E296091 entity
Predicate neighboringCommune P28600 FINISHED
Object Renca E414164 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: Renca | Statement: [Quinta Normal, neighboringCommune, Renca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Renca
Context triple: [Quinta Normal, neighboringCommune, 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. Anejima
    Anejima is a small, uninhabited Japanese island that forms part of the remote Mukojima subgroup in the Ogasawara (Bonin) Islands chain.
  • C. Rancaekek
    Rancaekek is a suburban district in West Java, Indonesia, known as a growing residential and industrial area on the eastern outskirts of Bandung.
  • D. 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.
  • E. Hita
    Hita is a historic town in the province of Guadalajara, Spain, known for its medieval architecture and literary associations.
  • 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_69d6ad9e653c8190b1473c860ee53dae completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d93fd33f048190b205fd21dc513f6a completed April 10, 2026, 6:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6347e27b4819085494babfe180488 completed May 2, 2026, 5:29 p.m.
Created at: April 8, 2026, 9:54 p.m.