Triple

T11239468
Position Surface form Disambiguated ID Type / Status
Subject Zipolite E266031 entity
Predicate hasNearbyTown P3883 FINISHED
Object Mazunte E272052 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: Mazunte | Statement: [Zipolite, hasNearbyTown, Mazunte]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mazunte
Context triple: [Zipolite, hasNearbyTown, Mazunte]
  • A. Mazunte chosen
    Mazunte is a small, laid-back beach town on Mexico’s Oaxacan coast, known for its sea turtle conservation center, eco-tourism, and scenic Pacific shoreline.
  • B. Atalaya
    Atalaya is a small Peruvian river port town in the Amazon rainforest, serving as a regional hub for transport and trade.
  • C. Copala
    Copala is a coastal town in the Costa Chica region of Guerrero, Mexico, known for its Afro-Mexican culture and Pacific shoreline.
  • D. Caibarién
    Caibarién is a coastal town and municipality in central Cuba known historically for its fishing industry and nearby keys.
  • E. Pacasmayo
    Pacasmayo is a coastal city in northern Peru known for its long pier, surfing beaches, and colonial-era architecture.
  • 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_69d6aac656d48190b275efaa7d6074ee completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e918375081908c2a7ccb50cbf331 completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4ad6e9390819085d10635cb039f85 completed April 19, 2026, 10:24 a.m.
Created at: April 8, 2026, 9:30 p.m.