Triple
T12201818
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holiday Styles |
E290733
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Styles Pinero |
E739687
|
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: Styles Pinero | Statement: [Holiday Styles, alsoKnownAs, Styles Pinero]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Styles Pinero Context triple: [Holiday Styles, alsoKnownAs, Styles Pinero]
-
A.
Pino
Pino is the former historic name of the present-day Town of Loomis in Placer County, California.
-
B.
Pino
Pino is an Italian diminutive form of the given name Giuseppe, commonly used as a familiar or affectionate nickname.
-
C.
El Pincha
El Pincha is the traditional nickname of Argentine football club Estudiantes de La Plata, reflecting its historic identity and fan culture.
-
D.
Piñero
chosen
Piñero is a 2001 biographical drama film in which Benjamin Bratt portrays the life and turbulent career of Nuyorican poet and playwright Miguel Piñero.
-
E.
Piñol
Piñol is a Spanish-language surname historically associated with prominent families in Central America.
- 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_69d6ab65923081909acfc61b7a612233 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91c7b97408190a11ea37cc6edf18c |
completed | April 10, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60a982e308190979245ac9643465a |
completed | May 2, 2026, 2:30 p.m. |
Created at: April 8, 2026, 9:51 p.m.