Triple

T16079246
Position Surface form Disambiguated ID Type / Status
Subject Loayza Province E390058 entity
Predicate seat P75 FINISHED
Object Luribay E1193024 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: Luribay | Statement: [Loayza Province, seat, Luribay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luribay
Context triple: [Loayza Province, seat, Luribay]
  • A. Luribay chosen
    Luribay is a small town in Bolivia known as an agricultural center, particularly for its vineyards and wine production, in the Loayza Province of the La Paz Department.
  • B. Roura
    Roura is a commune in French Guiana known for its rainforest landscapes and proximity to the Kaw-Roura Marshland Nature Reserve.
  • C. Barbalha
    Barbalha is a municipality in northeastern Brazil known for its traditional cultural festivals and location in the state of Ceará.
  • D. Morungaba
    Morungaba is a small municipality in the state of São Paulo, Brazil, known for its rural landscapes and integration into the economically significant Campinas metropolitan area.
  • E. Guiguinto
    Guiguinto is a municipality in the province of Bulacan in the Philippines, known for its rapid urbanization and ornamental plant industry.
  • 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_69d86daf32ec8190a8c0466c8f49c3c0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e18448bebc8190b0e84b1da097bf8b completed April 17, 2026, 12:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffeb917b008190b1680b347cfa0892 completed May 10, 2026, 2:21 a.m.
Created at: April 10, 2026, 4:57 a.m.