Triple

T14551847
Position Surface form Disambiguated ID Type / Status
Subject Gironella E341436 entity
Predicate hasNeighbouringMunicipality P224 FINISHED
Object Casserres E878560 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: Casserres | Statement: [Gironella, hasNeighbouringMunicipality, Casserres]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Casserres
Context triple: [Gironella, hasNeighbouringMunicipality, Casserres]
  • A. Casserres chosen
    Casserres is a municipality in the comarca of Berguedà in Catalonia, northeastern Spain.
  • B. Lavezares
    Lavezares is a coastal municipality in the province of Northern Samar in the Philippines, known for its fishing communities and island landscapes.
  • C. Yssingeaux
    Yssingeaux is a commune in south-central France that serves as an administrative and service center in the Haute-Loire department.
  • D. Josselin
    Josselin is a given name and surname of French origin, used as a variant of Jocelyn.
  • E. Serques
    Serques is a small commune in the Pas-de-Calais department in northern France, situated within the administrative area of Saint-Omer.
  • 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_69d822db9c8481908213ceb39585f792 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb2ee34208190bf040a513767c958 completed April 14, 2026, 9:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd8ab7d698819085fd81d7b6f96317 completed May 8, 2026, 7:03 a.m.
Created at: April 10, 2026, 1:23 a.m.