Triple

T14903873
Position Surface form Disambiguated ID Type / Status
Subject Camí de Quart E360076 entity
Predicate connects P390 FINISHED
Object Quart de Poblet E1042339 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: Quart de Poblet | Statement: [Camí de Quart, connects, Quart de Poblet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Quart de Poblet
Context triple: [Camí de Quart, connects, Quart de Poblet]
  • A. Quart de Poblet chosen
    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.
  • B. Pedralbes
    Pedralbes is an affluent residential neighborhood in Barcelona known for its upscale homes, green spaces, and prestigious educational institutions.
  • C. Banyoles
    Banyoles is a town in Catalonia, Spain, best known for its large natural lake and scenic surroundings.
  • D. 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.
  • E. Pla d'Urgell
    Pla d'Urgell is a comarca (county) in the inland plains of Catalonia, Spain, known for its irrigated agriculture and small rural towns.
  • 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_69d827980cbc8190a0c569ae3940a1d9 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69ded60b24008190bd272c0d61329400 completed April 15, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe968a17188190bced83ed1006e020 completed May 9, 2026, 2:06 a.m.
Created at: April 10, 2026, 2:12 a.m.