Triple
T2011714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don Quixote |
E43700
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Sancho Panza |
E43702
|
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: Sancho Panza | Statement: [Don Quixote, mainCharacter, Sancho Panza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sancho Panza Context triple: [Don Quixote, mainCharacter, Sancho Panza]
-
A.
Sancho Panza
chosen
Sancho Panza is the loyal, down-to-earth squire and comic foil to the idealistic knight-errant Don Quixote in Miguel de Cervantes' classic novel.
-
B.
Sancho
Sancho is a neighborhood or district within the Brazilian coastal city of Recife.
-
C.
Sancio Cabot
Sancio Cabot was a son of the Italian explorer John Cabot, likely associated with his father's late 15th-century voyages of discovery under the English flag.
-
D.
Quichotte
Quichotte is a 2019 novel by Salman Rushdie that reimagines Cervantes’ Don Quixote in contemporary America, blending satire, metafiction, and social commentary.
-
E.
Pánfilo
Pánfilo is a masculine given name of Spanish origin, historically associated with the conquistador Pánfilo de Narváez.
- 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_69a88716e9f08190946313fdc949e3cf |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb8b150a8819096c919465fd91ab5 |
completed | March 7, 2026, 5:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae0ae85ed48190adc75fd17b17f6c9 |
completed | March 8, 2026, 11:48 p.m. |
Created at: March 4, 2026, 7:37 p.m.