Triple
T19921983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pascual Pérez |
E478817
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | Pascualito |
—
|
NE NERFINISHED |
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: Pascualito | Statement: [Pascual Pérez, nickname, Pascualito]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pascualito Context triple: [Pascual Pérez, nickname, Pascualito]
-
A.
Pascual
chosen
Pascual is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
-
B.
Alvarito
Alvarito is a Spanish diminutive form of the given name Álvaro, typically used as an affectionate nickname.
-
C.
Blanquillos
Blanquillos is a popular nickname for the Spanish football club Real Zaragoza, referring to the team’s traditional white kit.
-
D.
Balbuena
Balbuena is a metro station on Mexico City’s Line 1 serving the Balbuena neighborhood in the eastern part of the city.
-
E.
Pacheco
Pacheco is a Spanish surname borne by various notable figures in fields such as politics, arts, and sports.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e521855c8190b41871700afc8d6a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e659c6919c8190a96106532580b6b6 |
completed | April 20, 2026, 4:52 p.m. |
Created at: April 10, 2026, 1:53 p.m.