Triple
T6426385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diego Velázquez de Cuéllar |
E128067
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | de Cuéllar |
E128067
|
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: de Cuéllar | Statement: [Diego Velázquez de Cuéllar, familyName, de Cuéllar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: de Cuéllar Context triple: [Diego Velázquez de Cuéllar, familyName, de Cuéllar]
-
A.
de Cuéllar
chosen
de Cuéllar is a Spanish surname historically associated with figures such as the conquistador Diego Velázquez de Cuéllar.
-
B.
Simancas
Simancas is a historic town in Spain renowned for its royal archive, which houses some of the country’s most important state documents.
-
C.
Calvero
Calvero is the aging, once-famous clown portrayed by Charlie Chaplin in the 1952 film "Limelight," struggling with obscurity and seeking redemption through helping a young dancer.
-
D.
de Benalcázar
De Benalcázar is the surname of Sebastián de Benalcázar, a 16th-century Spanish conquistador known for his expeditions and role in the conquest of parts of present-day Colombia and Ecuador.
-
E.
Argüelles
Argüelles is a Madrid Metro station serving the Argüelles neighborhood, providing an interchange between several central metro lines.
- 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_69c00838de888190af2eec0b80495efa |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0691f944c81909d4e5d8ef9e494b6 |
completed | March 22, 2026, 10:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c640e339108190bbb74c688de574cc |
completed | March 27, 2026, 8:33 a.m. |
Created at: March 22, 2026, 4:44 p.m.