Triple

T14853183
Position Surface form Disambiguated ID Type / Status
Subject Municipal Chamber of Horta E349282 entity
Predicate jurisdiction P82 FINISHED
Object Horta E69958 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: Horta | Statement: [Municipal Chamber of Horta, jurisdiction, Horta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Horta
Context triple: [Municipal Chamber of Horta, jurisdiction, Horta]
  • A. Horta
    Horta is a Barcelona Metro station serving the Horta neighborhood in the city’s northeastern district.
  • B. Horta chosen
    Horta is a coastal city on the island of Faial in the Azores, known for its historic transatlantic harbor and vibrant marina frequented by ocean-crossing yachts.
  • C. Sabrosa
    Sabrosa is a small municipality in Portugal’s Douro region, historically notable as the birthplace of explorer Ferdinand Magellan.
  • D. Figueira da Horta
    Figueira da Horta is a small village located on the island of Maio in Cape Verde.
  • E. Sernancelhe
    Sernancelhe is a municipality in northern Portugal known for its historic granite architecture, religious heritage, and scenic rural landscapes.
  • 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_69d822ed7e1881909b90fca143ad7e34 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded44318f0819080b6c599f2d3474f completed April 14, 2026, 11:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69fed31a49d88190a200c427fe02616f completed May 9, 2026, 6:24 a.m.
Created at: April 10, 2026, 1:54 a.m.