Triple

T9519959
Position Surface form Disambiguated ID Type / Status
Subject Cilla Black E229619 entity
Predicate placeOfDeath P21 FINISHED
Object Estepona E143546 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: Estepona | Statement: [Cilla Black, placeOfDeath, Estepona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Estepona
Context triple: [Cilla Black, placeOfDeath, Estepona]
  • A. Estepona chosen
    Estepona is a coastal resort town on Spain’s Costa del Sol, known for its Mediterranean beaches, marina, and whitewashed old town.
  • B. Benalmádena
    Benalmádena is a coastal resort town on Spain’s Costa del Sol, known for its beaches, marina, and tourist attractions near Málaga.
  • C. Torremolinos
    Torremolinos is a popular seaside resort town on Spain’s Costa del Sol, known for its beaches, nightlife, and tourism-focused economy.
  • D. Marbella
    Marbella is a popular resort city on Spain’s Costa del Sol, known for its Mediterranean beaches, luxury marinas, upscale nightlife, and historic old town.
  • E. Fuengirola
    Fuengirola is a popular coastal resort town on Spain’s Costa del Sol, known for its long sandy beaches, tourism infrastructure, and proximity to Málaga.
  • 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_69ca847870a881909d8d751a7d29da39 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9883c5c48190a6583921afe9730a completed April 1, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69d14c1f10748190a36d2092d593be97 completed April 4, 2026, 5:36 p.m.
Created at: March 30, 2026, 7:59 p.m.