Triple

T11481379
Position Surface form Disambiguated ID Type / Status
Subject Tom Sharpe E272157 entity
Predicate placeOfDeath P21 FINISHED
Object Llafranc E790644 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: Llafranc | Statement: [Tom Sharpe, placeOfDeath, Llafranc]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Llafranc
Context triple: [Tom Sharpe, placeOfDeath, Llafranc]
  • A. Llafranc chosen
    Llafranc is a picturesque coastal village in Catalonia, Spain, known for its sandy beach, seafront promenade, and relaxed Mediterranean atmosphere.
  • B. Viladrau
    Viladrau is a small Catalan town in northeastern Spain, known for its natural springs and location within the Montseny Natural Park.
  • C. Moianès
    Moianès is a comarca (county) in central Catalonia, Spain, known for its rural landscapes, small historic towns, and karstic plateau terrain.
  • D. Forcalquier
    Forcalquier is a historic Provençal town in southeastern France known for its medieval architecture, hilltop citadel, and traditional markets.
  • E. Fages
    Fages is a Spanish surname most notably associated with Pedro Fages, an 18th-century Spanish soldier and colonial administrator in California.
  • 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_69d6aae0c8d881908a5a360c0be3242e completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d85a1d86b88190b180f6b0d0a27029 completed April 10, 2026, 2:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69e604410fbc819098b101c029b63525 completed April 20, 2026, 10:47 a.m.
Created at: April 8, 2026, 9:36 p.m.