Triple

T10294739
Position Surface form Disambiguated ID Type / Status
Subject LATAM Ecuador E241453 entity
Predicate hasFocusCity P1295 FINISHED
Object Guayaquil E8988 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: Guayaquil | Statement: [LATAM Ecuador, hasFocusCity, Guayaquil]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guayaquil
Context triple: [LATAM Ecuador, hasFocusCity, Guayaquil]
  • A. Guayaquil chosen
    Guayaquil is a major Pacific port city in southwestern Ecuador and the country’s principal commercial and industrial center.
  • B. Quito
    Quito is the high-altitude Andean city that serves as Ecuador’s political and cultural center, renowned for its well-preserved colonial historic center and dramatic mountain setting.
  • C. Esmeraldas
    Esmeraldas is a coastal city and province in northwestern Ecuador known for its Afro-Ecuadorian culture, beaches, and important oil and port industries.
  • D. Cumaná
    Cumaná is a historic coastal city in northeastern Venezuela, recognized as one of the oldest continuously inhabited European-founded settlements in the Americas.
  • E. Lima
    Lima is a station on Buenos Aires’ historic Underground Line A, serving passengers in the city’s central area.
  • 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_69d381aaafc08190af475ef58dc16aba completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d2d5e0f88190be3e23ba2511a1e9 completed April 7, 2026, 9:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69d89f3814dc8190b9da0ee680209d51 completed April 10, 2026, 6:56 a.m.
Created at: April 6, 2026, 11:42 a.m.