Triple

T13303200
Position Surface form Disambiguated ID Type / Status
Subject Gironès E316865 entity
Predicate contains P35 FINISHED
Object Cassà de la Selva E1028930 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: Cassà de la Selva | Statement: [Gironès, contains, Cassà de la Selva]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cassà de la Selva
Context triple: [Gironès, contains, Cassà de la Selva]
  • A. Cassà de la Selva chosen
    Cassà de la Selva is a municipality in the province of Girona, Catalonia, Spain, known for its cork industry and location near the Costa Brava.
  • B. Sant Celoni
    Sant Celoni is a town in Catalonia, Spain, located northeast of Barcelona in the Vallès Oriental comarca, known as a local commercial and transport hub between the Montseny and Montnegre natural areas.
  • C. Les Cabanyes
    Les Cabanyes is a small municipality in the Alt Penedès comarca of Catalonia, Spain, known for its rural character and surrounding vineyards.
  • D. Torroella de Montgrí
    Torroella de Montgrí is a historic town in Catalonia, Spain, known for its medieval architecture and its location near the Montgrí Massif and the Costa Brava.
  • E. Pedralbes
    Pedralbes is an affluent residential neighborhood in Barcelona known for its upscale homes, green spaces, and prestigious educational institutions.
  • 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_69d806b40ab4819094adf6c374f4811a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d990a60eb08190bf0dc098ca7dc342 completed April 11, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69f716e161008190a48275ef54225d56 completed May 3, 2026, 9:35 a.m.
Created at: April 9, 2026, 9:28 p.m.