Triple

T5849217
Position Surface form Disambiguated ID Type / Status
Subject Iker Casillas E129986 entity
Predicate familyName P18 FINISHED
Object Casillas E129986 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: Casillas | Statement: [Iker Casillas, familyName, Casillas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Casillas
Context triple: [Iker Casillas, familyName, Casillas]
  • A. Iker Casillas chosen
    Iker Casillas is a legendary Spanish goalkeeper widely regarded as one of the greatest in football history, known for his long and successful career with Real Madrid and the Spanish national team.
  • B. José Salas
    José Salas was a figure significant enough in Chilean or regional maritime history or exploration to have the remote Pacific island of Isla Salas y Gómez named in his honor.
  • C. Ramos
    Ramos is a municipality in the Philippine province of Tarlac known for its predominantly agricultural economy and rural communities.
  • D. Raúl González
    Raúl González is a legendary Spanish striker best known for his prolific goal-scoring and long, trophy-laden career as a symbol of Real Madrid.
  • E. Cazorla
    Cazorla is a historic town in Andalusia, southern Spain, known as a gateway to the Sierra de Cazorla Natural Park and for its medieval castle and scenic mountain setting.
  • 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_69c0084de39081909eb34e6bed74215a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c035145a0c8190941945a83a3f2416 completed March 22, 2026, 6:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0b1007bbc81908963d3d14c9210c5 completed March 23, 2026, 3:18 a.m.
Created at: March 22, 2026, 3:55 p.m.