Triple

T19854051
Position Surface form Disambiguated ID Type / Status
Subject Elisenda de Montcada E477083 entity
Predicate associatedWith P37 FINISHED
Object Pedralbes NE NERFINISHED

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: Pedralbes | Statement: [Elisenda de Montcada, associatedWith, Pedralbes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pedralbes
Context triple: [Elisenda de Montcada, associatedWith, Pedralbes]
  • A. Pedralbes chosen
    Pedralbes is an affluent residential neighborhood in Barcelona known for its upscale homes, green spaces, and prestigious educational institutions.
  • B. Pedralba
    Pedralba is a municipality in the province of Valencia, Spain, known for its rural landscape and location along the Turia River.
  • C. Quart de Poblet
    Quart de Poblet is a municipality in the province of Valencia, Spain, known for its proximity to the city of Valencia and its role within the metropolitan area.
  • D. Banyoles
    Banyoles is a town in Catalonia, Spain, best known for its large natural lake and scenic surroundings.
  • E. Noguera Pallaresa
    Noguera Pallaresa is a river in the Catalan Pyrenees of northeastern Spain, renowned for its whitewater rafting and kayaking.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e51d39d081909bcfafeaaf3d2fcc completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6586aa1dc8190b6cfe051a57e338b completed April 20, 2026, 4:46 p.m.
Created at: April 10, 2026, 1:51 p.m.