Triple
T8844250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Enrique Cerezo |
E210463
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Enrique Cerezo |
E210463
|
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: Enrique Cerezo | Statement: [Enrique Cerezo, name, Enrique Cerezo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Enrique Cerezo Context triple: [Enrique Cerezo, name, Enrique Cerezo]
-
A.
Enrique Cerezo
chosen
Enrique Cerezo is a Spanish film producer and businessman best known for serving as the long-time president of Atlético de Madrid football club.
-
B.
Alfredo Rodríguez Ballón
Alfredo Rodríguez Ballón was a Peruvian aviator regarded as a pioneering figure in the country’s civil aviation history.
-
C.
José Rijo
José Rijo is a former Dominican Major League Baseball pitcher best known for his standout performances with the Cincinnati Reds, including his dominant role in their 1990 championship run.
-
D.
Armando Benítez
Armando Benítez is a former Major League Baseball relief pitcher from the Dominican Republic, best known for his powerful fastball and closing stints with teams like the Baltimore Orioles and New York Mets.
-
E.
Luis Colina
Luis Colina is a film editor known for his work on the movie "Sugar Hill."
- 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_69ca838967bc8190b46c3c80a2887ea4 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc608a73c88190875409fef79ffc8a |
completed | April 1, 2026, 12:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc1c1488c8190ac7b6a13d3af8be6 |
completed | April 3, 2026, 1:33 p.m. |
Created at: March 30, 2026, 6:48 p.m.