Triple

T22698386
Position Surface form Disambiguated ID Type / Status
Subject Southern Ecuador E561246 entity
Predicate hasMajorCity P316 FINISHED
Object Machala 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: Machala | Statement: [Southern Ecuador, hasMajorCity, Machala]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Machala
Context triple: [Southern Ecuador, hasMajorCity, Machala]
  • A. Machala chosen
    Machala is a coastal city in southwestern Ecuador known as a major banana-exporting port and the capital of El Oro Province.
  • B. Moyobamba
    Moyobamba is a city in northern Peru known for its rich biodiversity, orchid gardens, and role as a commercial and cultural hub in the Amazonian highlands.
  • C. Talara
    Talara is a coastal city in northwestern Peru known for its important oil industry and nearby Pacific beaches.
  • D. Pucallpa
    Pucallpa is a major city in eastern Peru, located in the Amazon rainforest along the Ucayali River and serving as an important regional commercial and transportation hub.
  • E. Ancón District
    Ancón District is a coastal district in the northern part of Lima Province, Peru, known for its beaches and role as a popular seaside resort area.
  • 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_69e2454e615481909c177440be559d2c completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f178a008448190b393335704128fe8 completed April 29, 2026, 3:18 a.m.
Created at: April 17, 2026, 3:14 p.m.