Triple

T13970214
Position Surface form Disambiguated ID Type / Status
Subject El Carmen Canton E336040 entity
Predicate locatedIn P40 FINISHED
Object Manabí Province E65578 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: Manabí Province | Statement: [El Carmen Canton, locatedIn, Manabí Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manabí Province
Context triple: [El Carmen Canton, locatedIn, Manabí Province]
  • A. Manabí Province chosen
    Manabí Province is a coastal province in western Ecuador known for its Pacific beaches, fishing industry, and agricultural production.
  • B. Guayas Province
    Guayas Province is a coastal region in western Ecuador that includes the country’s largest city and main port, Guayaquil, and serves as a key economic and commercial hub.
  • C. La Vega Province
    La Vega Province is a central Dominican Republic province known for its fertile valleys, agricultural production, and the vibrant Carnival of La Vega.
  • D. Los Santos Province
    Los Santos Province is a largely rural region in southern Panama known for its agricultural production, folkloric traditions, and Pacific coastline.
  • E. Velasco Province
    Velasco Province is an administrative province in eastern Bolivia, located within the Santa Cruz Department and known for its vast lowland landscapes and rural communities.
  • 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_69d81c61f3508190aaf2ca0dc0002c59 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2e8daeac8190aadd4b3b60222482 completed April 14, 2026, 12:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcf7d691008190a38729d18de2bb91 completed May 7, 2026, 8:36 p.m.
Created at: April 9, 2026, 10:18 p.m.