Triple

T3111763
Position Surface form Disambiguated ID Type / Status
Subject Los Ríos Province E64967 entity
Predicate largestCity P235 FINISHED
Object Babahoyo E244448 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: Babahoyo | Statement: [Los Ríos Province, largestCity, Babahoyo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Babahoyo
Context triple: [Los Ríos Province, largestCity, Babahoyo]
  • A. Babahoyo chosen
    Babahoyo is a city in western Ecuador that serves as the capital of Los Ríos Province and an important agricultural and commercial center.
  • B. Soacha
    Soacha is a rapidly growing industrial and residential city in central Colombia, located just southwest of Bogotá in the department of Cundinamarca.
  • C. Cajicá
    Cajicá is a Colombian town and municipality in the department of Cundinamarca, known for its colonial heritage and proximity to Bogotá.
  • D. Tumaco
    Tumaco is a coastal city and municipality in southwestern Colombia, known for its Afro-Colombian culture, Pacific beaches, and rich pre-Hispanic goldworking heritage.
  • E. Tarapoto
    Tarapoto is a city in northern Peru known as a gateway to the Amazon rainforest and a regional hub for tourism and commerce.
  • 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_69ad857eeaf48190b34ebfdaa7a264cf completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada43b0b3c8190a828c9cfcf730ed9 completed March 8, 2026, 4:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b24b2a9b648190a74c7691cc7a4959 completed March 12, 2026, 5:12 a.m.
Created at: March 8, 2026, 3:04 p.m.