Triple

T14853201
Position Surface form Disambiguated ID Type / Status
Subject Municipal Chamber of Horta E349282 entity
Predicate seatOfGovernment P761 FINISHED
Object Horta city 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 city | Statement: [Municipal Chamber of Horta, seatOfGovernment, Horta city]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Horta city
Context triple: [Municipal Chamber of Horta, seatOfGovernment, Horta city]
  • 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. Figueira da Horta
    Figueira da Horta is a small village located on the island of Maio in Cape Verde.
  • D. Ponta Delgada
    Ponta Delgada is the largest city and main economic and administrative center of the Azores archipelago in Portugal, located on the island of São Miguel.
  • E. Vila do Conde
    Vila do Conde is a coastal city in northern Portugal known for its historic shipbuilding heritage, beaches, and well-preserved medieval architecture.
  • 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_69fee5dee8988190b80cb487c12bfc2d completed May 9, 2026, 7:44 a.m.
Created at: April 10, 2026, 1:54 a.m.