Triple

T10334536
Position Surface form Disambiguated ID Type / Status
Subject Tab Ramos E242966 entity
Predicate playedFor P2170 FINISHED
Object Figueres E42935 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: Figueres | Statement: [Tab Ramos, playedFor, Figueres]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Figueres
Context triple: [Tab Ramos, playedFor, Figueres]
  • A. Figueres chosen
    Figueres is a town in Catalonia, Spain, best known as the birthplace of surrealist artist Salvador Dalí and home to the Dalí Theatre-Museum.
  • B. Besalú
    Besalú is a well-preserved medieval town in Catalonia, Spain, renowned for its Romanesque architecture and iconic 12th-century stone bridge.
  • C. Palamós
    Palamós is a coastal town and popular tourist destination on Spain’s Costa Brava, known for its fishing port, beaches, and seafood cuisine.
  • D. Girona
    Girona is a historic city in northeastern Catalonia, Spain, known for its well-preserved medieval architecture, walled Old Quarter, and prominent cathedral.
  • E. Tàrrega
    Tàrrega is a historic town in Catalonia, Spain, known for its cultural festivals and medieval 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_69d381af787481908bc401325c760a88 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4dfc366b481909c49f199892e9d42 completed April 7, 2026, 10:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69d8dc02ddc481908ab0ea2d1da04dc3 completed April 10, 2026, 11:16 a.m.
Created at: April 6, 2026, 11:53 a.m.