Triple

T18668596
Position Surface form Disambiguated ID Type / Status
Subject Carnavalcázar E456406 entity
Predicate region P40 FINISHED
Object La Mancha NE NERFINISHED

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: La Mancha | Statement: [Carnavalcázar, region, La Mancha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Mancha
Context triple: [Carnavalcázar, region, La Mancha]
  • A. La Mancha chosen
    La Mancha is a historic, arid region in central Spain best known as the home of Cervantes’ fictional knight-errant Don Quixote.
  • B. El gallardo español
    El gallardo español is a play by Miguel de Cervantes, notable as one of his lesser-known dramatic works included among his unperformed comedies and interludes.
  • C. El caballero de Olmedo
    El caballero de Olmedo is a celebrated Spanish Golden Age tragicomedy by Lope de Vega that dramatizes love, honor, and fatal destiny in rural Castile.
  • D. Manuel del Campo
    Manuel del Campo was a Mexican-born film editor and writer best known for his work in Hollywood and for being the second husband of actress Mary Astor.
  • E. El Burgo de Osma
    El Burgo de Osma is a historic town in the province of Soria, Spain, known for its well-preserved medieval architecture and prominent role as a religious and cultural center.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d38f72b4819090a935175d9ca8af completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e556b0502881909ea05f2746163746 completed April 19, 2026, 10:26 p.m.
Created at: April 10, 2026, 11:48 a.m.