Triple

T9520881
Position Surface form Disambiguated ID Type / Status
Subject The Priest E229639 entity
Predicate hasFriend P8712 FINISHED
Object Don Quixote E43700 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: Don Quixote | Statement: [The Priest, hasFriend, Don Quixote]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Don Quixote
Context triple: [The Priest, hasFriend, Don Quixote]
  • A. Don Quixote chosen
    Don Quixote is a classic Spanish novel by Miguel de Cervantes that follows the misadventures of an idealistic would-be knight and his squire as they pursue chivalric fantasies in a prosaic world.
  • B. Don Quixote
    Don Quixote is a tone poem by Richard Strauss that musically depicts the adventures and delusions of Cervantes’ iconic knight-errant through a series of symphonic variations.
  • C. 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.
  • D. Lazarillo de Tormes
    Lazarillo de Tormes is a seminal anonymous Spanish novella that inaugurated the picaresque genre by depicting the misadventures of a low-born rogue navigating a corrupt society.
  • E. La Mancha
    La Mancha is a historic, arid region in central Spain best known as the home of Cervantes’ fictional knight-errant Don Quixote.
  • 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_69d2e4fa938881908253aed52870210d completed April 5, 2026, 10:40 p.m.
Created at: March 30, 2026, 7:59 p.m.