Triple
T3096847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sancio Cabot |
E64615
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Sancio |
E64615
|
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: Sancio | Statement: [Sancio Cabot, givenName, Sancio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sancio Context triple: [Sancio Cabot, givenName, Sancio]
-
A.
Sancio Cabot
chosen
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.
-
B.
Sancho
Sancho is a neighborhood or district within the Brazilian coastal city of Recife.
-
C.
Sancho Panza
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.
-
D.
Alonso Quixano
Alonso Quixano is the deluded Spanish nobleman who, after obsessively reading chivalric romances, transforms himself into the knight-errant Don Quixote in Miguel de Cervantes’ classic novel.
-
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_69ad857dc98481909e585dc3372e3ed5 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada23cbe3c8190b7ec5cfd464a1ca8 |
completed | March 8, 2026, 4:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b20f563524819084ae75c024b8291d |
completed | March 12, 2026, 12:56 a.m. |
Created at: March 8, 2026, 3:03 p.m.