Triple
T13364895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benítez |
E318912
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Roberto Benítez
Roberto Benítez is a Paraguayan professional boxer known for competing in the lower weight divisions.
|
E1046900
|
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: Roberto Benítez | Statement: [Benítez, hasNotableBearer, Roberto Benítez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roberto Benítez Context triple: [Benítez, hasNotableBearer, Roberto Benítez]
-
A.
Ricardo Benítez
Ricardo Benítez is a notable individual recognized for achievements significant enough to be associated with the surname Benítez.
-
B.
Rafael Benítez
Rafael Benítez is a Spanish football manager renowned for his tactical acumen and success in European competitions, including winning the UEFA Champions League with Liverpool.
-
C.
Derlis Benítez
Derlis Benítez is a Paraguayan former professional footballer known for playing as a forward for clubs in Paraguay and abroad.
-
D.
Manuel Benítez
Manuel Benítez is a Spanish former bullfighter and actor, widely known by his ring name "El Cordobés."
-
E.
Miguel Herrera
Miguel Herrera is a Mexican football manager and former defender best known for coaching both Club América to multiple titles and the Mexico national team at the 2014 FIFA World Cup.
- 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: Roberto Benítez Triple: [Benítez, hasNotableBearer, Roberto Benítez]
Generated description
Roberto Benítez is a Paraguayan professional boxer known for competing in the lower weight divisions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Roberto Benítez Target entity description: Roberto Benítez is a Paraguayan professional boxer known for competing in the lower weight divisions.
-
A.
Ricardo Benítez
Ricardo Benítez is a notable individual recognized for achievements significant enough to be associated with the surname Benítez.
-
B.
Rafael Benítez
Rafael Benítez is a Spanish football manager renowned for his tactical acumen and success in European competitions, including winning the UEFA Champions League with Liverpool.
-
C.
Derlis Benítez
Derlis Benítez is a Paraguayan former professional footballer known for playing as a forward for clubs in Paraguay and abroad.
-
D.
Manuel Benítez
Manuel Benítez is a Spanish former bullfighter and actor, widely known by his ring name "El Cordobés."
-
E.
Miguel Herrera
Miguel Herrera is a Mexican football manager and former defender best known for coaching both Club América to multiple titles and the Mexico national team at the 2014 FIFA World Cup.
- 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_69d806b7bbac8190b85278c87fa7aff3 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69da628c71ac81908cfa36342077766e |
completed | April 11, 2026, 3:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75d8322ac8190a9830d9ca92f455f |
completed | May 3, 2026, 2:36 p.m. |
| NEDg | Description generation | batch_69f75f4352d48190ab57ab8ee57dba13 |
completed | May 3, 2026, 2:44 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f75f9fced081909962a881e469d3c4 |
completed | May 3, 2026, 2:45 p.m. |
Created at: April 9, 2026, 9:32 p.m.