Triple
T16906838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baloncesto Fuenlabrada |
E424584
|
entity |
| Predicate | hasNotablePlayer |
P9730
|
FINISHED |
| Object |
Saúl Blanco
Saúl Blanco is a Spanish professional basketball player known for his career in the Liga ACB, where he played as a versatile guard-forward for several teams.
|
E1357263
|
NE FINISHED |
How this triple was built (4 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: Saúl Blanco | Statement: [Baloncesto Fuenlabrada, hasNotablePlayer, Saúl Blanco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saúl Blanco Context triple: [Baloncesto Fuenlabrada, hasNotablePlayer, Saúl Blanco]
-
A.
Roberto Álamo
Roberto Álamo is a Spanish actor known for his work in film, television, and theater, including prominent roles in acclaimed Spanish cinema.
-
B.
Saul Herrera
Saul Herrera is an actor known for his role in the television series "Models Inc."
-
C.
Rafael Salmerón
Rafael Salmerón is a Spanish author and illustrator known for his work in children's and young adult literature.
-
D.
Luis Salmerón
Luis Salmerón is a former Argentine professional footballer known for his role as a forward with several clubs in South America.
-
E.
Jorge Huerta
Jorge Huerta is a prominent Chicano theater scholar, director, and educator known for his pioneering work in documenting and advancing Latino/a performance in the United States.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Saúl Blanco Triple: [Baloncesto Fuenlabrada, hasNotablePlayer, Saúl Blanco]
Generated description
Saúl Blanco is a Spanish professional basketball player known for his career in the Liga ACB, where he played as a versatile guard-forward for several teams.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Saúl Blanco Target entity description: Saúl Blanco is a Spanish professional basketball player known for his career in the Liga ACB, where he played as a versatile guard-forward for several teams.
-
A.
Roberto Álamo
Roberto Álamo is a Spanish actor known for his work in film, television, and theater, including prominent roles in acclaimed Spanish cinema.
-
B.
Saul Herrera
Saul Herrera is an actor known for his role in the television series "Models Inc."
-
C.
Rafael Salmerón
Rafael Salmerón is a Spanish author and illustrator known for his work in children's and young adult literature.
-
D.
Luis Salmerón
Luis Salmerón is a former Argentine professional footballer known for his role as a forward with several clubs in South America.
-
E.
Jorge Huerta
Jorge Huerta is a prominent Chicano theater scholar, director, and educator known for his pioneering work in documenting and advancing Latino/a performance in the United States.
- F. None of above. chosen
Provenance (5 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_69d889da3e8c8190a2b118f383f0beac |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3ca39f9b08190b15106c6caf895ec |
completed | April 18, 2026, 6:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05d32f1ee88190b0a215dc78024d62 |
completed | May 14, 2026, 1:50 p.m. |
| NEDg | Description generation | batch_6a05d56219508190baead365509166a3 |
completed | May 14, 2026, 2 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a05d6537b9c8190918a56b74c675f7e |
completed | May 14, 2026, 2:04 p.m. |
Created at: April 10, 2026, 5:30 a.m.