Triple

T10769557
Position Surface form Disambiguated ID Type / Status
Subject Raval Campus E254038 entity
Predicate district P2709 FINISHED
Object Raval E884797 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: Raval | Statement: [Raval Campus, district, Raval]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Raval
Context triple: [Raval Campus, district, Raval]
  • A. Raval chosen
    Raval is a historic and culturally diverse neighborhood in central Barcelona, Spain, known for its vibrant street life, arts scene, and mix of old and new architecture.
  • B. Matadepera
    Matadepera is a municipality in the Vallès Occidental comarca of Catalonia, Spain, known for its residential character and proximity to the Sant Llorenç del Munt i l'Obac Natural Park.
  • C. Barrio Bajo
    Barrio Bajo is the lower neighborhood district of Trévélez, a mountain village in Spain’s Alpujarras region.
  • D. El Realejo
    El Realejo is a historic coastal town and former colonial port in northwestern Nicaragua.
  • E. Barri Vell
    Barri Vell is the historic old quarter of Girona, known for its medieval streets, ancient city walls, and well-preserved architectural heritage.
  • 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_69d6aa5f54f4819082d0bbcb6f8797e6 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d732307fb88190ba1447f68523c58a completed April 9, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69de55cbbecc81908c2ddf2739ce7ffe completed April 14, 2026, 2:57 p.m.
Created at: April 8, 2026, 9:16 p.m.