Triple

T13239344
Position Surface form Disambiguated ID Type / Status
Subject Ter E315238 entity
Predicate hasMouthNear P350 FINISHED
Object Torroella de Montgrí E813729 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: Torroella de Montgrí | Statement: [Ter, hasMouthNear, Torroella de Montgrí]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Torroella de Montgrí
Context triple: [Ter, hasMouthNear, Torroella de Montgrí]
  • A. Torroella de Montgrí chosen
    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.
  • B. Torrelles de Llobregat
    Torrelles de Llobregat is a small municipality in the Baix Llobregat comarca of Catalonia, Spain, known for its hilly landscape and proximity to Barcelona.
  • C. Pedralbes
    Pedralbes is an affluent residential neighborhood in Barcelona known for its upscale homes, green spaces, and prestigious educational institutions.
  • D. Montornès del Vallès
    Montornès del Vallès is a municipality in the Vallès Oriental comarca of Catalonia, Spain, situated within the greater Barcelona metropolitan area.
  • E. Celrà
    Celrà is a municipality in the province of Girona, Catalonia, Spain, known for its rural character and proximity to the city of Girona.
  • 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_69d806b1072881909e46bd212259c5f0 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98d5850ac8190849a51da39efe5be completed April 10, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7305c5f8081908bbe19f2a644acc5 completed May 3, 2026, 11:24 a.m.
Created at: April 9, 2026, 9:23 p.m.