Triple
T3286549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danny Trejo |
E68994
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Danny Trejo |
E68994
|
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: Danny Trejo | Statement: [Danny Trejo, name, Danny Trejo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Danny Trejo Context triple: [Danny Trejo, name, Danny Trejo]
-
A.
Danny Trejo
chosen
Danny Trejo is an American character actor known for his tough-guy roles in action and crime films, often portraying hardened criminals or antiheroes.
-
B.
Antonio Fargas
Antonio Fargas is an American character actor best known for his flamboyant and comedic roles in 1970s blaxploitation films and the TV series "Starsky & Hutch."
-
C.
Raymond Cruz
Raymond Cruz is an American actor best known for his intense portrayals of law enforcement officers and criminals in television series such as "The Closer" and "Breaking Bad."
-
D.
Miguel Ángel Ramírez
Miguel Ángel Ramírez is a Spanish football manager known for his tactical work in South American and Major League Soccer clubs.
-
E.
Benjamin Bratt
Benjamin Bratt is an American actor known for his roles in film and television, including prominent performances in projects like "Law & Order," "Miss Congeniality," and various dramatic and action films.
- 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_69ad859d45748190b0742408c954b39f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb05779d08190a5517951e71b1380 |
completed | March 8, 2026, 5:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2e85b6a1081908581b2040b8ce261 |
completed | March 12, 2026, 4:22 p.m. |
Created at: March 8, 2026, 3:10 p.m.