Triple
T2142914
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coco |
E46999
|
entity |
| Predicate | voiceActor |
P1507
|
FINISHED |
| Object | Benjamin Bratt |
E201657
|
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: Benjamin Bratt | Statement: [Coco, voiceActor, Benjamin Bratt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Benjamin Bratt Context triple: [Coco, voiceActor, Benjamin Bratt]
-
A.
Benjamin Bratt
chosen
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.
-
B.
Andre Braugher
Andre Braugher is an American actor acclaimed for his powerful dramatic roles and his Emmy-winning performances in both television and film.
-
C.
Michael Peña
Michael Peña is an American actor known for his versatile supporting roles in films such as "Crash," "Ant-Man," and "End of Watch."
-
D.
Dennis Haysbert
Dennis Haysbert is an American actor known for his deep voice and prominent roles in film and television, including "24," "Major League," and numerous commercial campaigns.
-
E.
Luke Goss
Luke Goss is an English actor and former drummer best known for his roles in genre films such as "Blade II" and "Hellboy II: The Golden Army."
- 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_69a88a1933e0819094f18426ed74180f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbe206db0819095772af5358dca55 |
completed | March 7, 2026, 5:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae51b63e4081908a5d87af5d17d3c4 |
completed | March 9, 2026, 4:51 a.m. |
Created at: March 4, 2026, 7:44 p.m.