Triple

T11633969
Position Surface form Disambiguated ID Type / Status
Subject Anta Province E276468 entity
Predicate hasUrbanCenter P2106 FINISHED
Object Anta E937187 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: Anta | Statement: [Anta Province, hasUrbanCenter, Anta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anta
Context triple: [Anta Province, hasUrbanCenter, Anta]
  • A. Anta chosen
    Anta is a town in southern Peru that serves as the administrative and commercial center of Anta Province in the Cusco Region.
  • B. Anta
    Anta is a subgroup within the Waic language cluster, representing one of its distinct linguistic or ethnic subdivisions.
  • C. Parea
    Parea is a small coastal village on the island of Huahine in French Polynesia, known for its tranquil beaches and traditional Polynesian atmosphere.
  • D. Horizonte
    Horizonte is a municipality in the state of Ceará in northeastern Brazil, known for its growing industrial sector and proximity to the Fortaleza metropolitan area.
  • E. Patagonia
    Patagonia is a sparsely populated region at the southern end of South America, renowned for its dramatic mountains, glaciers, and windswept plains shared by Chile and Argentina.
  • 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_69d6aafa51148190ab84940694c00235 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a25c0b00819095898d2b2445ecfb completed April 10, 2026, 7:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef82b8b1f48190aa6c78044d3570d1 completed April 27, 2026, 3:37 p.m.
Created at: April 8, 2026, 9:39 p.m.