Triple

T9520844
Position Surface form Disambiguated ID Type / Status
Subject Alonso Quixano E229638 entity
Predicate fictionalResidence P7550 FINISHED
Object La Mancha E227375 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: La Mancha | Statement: [Alonso Quixano, fictionalResidence, La Mancha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Mancha
Context triple: [Alonso Quixano, fictionalResidence, 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. 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.
  • D. Fuente del Quijote
    Fuente del Quijote is a fountain in Mexico City’s historic Alameda Central park that features imagery inspired by Miguel de Cervantes’ iconic character Don Quixote.
  • E. La Jara
    La Jara is a small town in southern Colorado that serves as the primary population and commercial center of Conejos County.
  • 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_69cd9884dd5c8190b69c178cb2ac75c2 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.