Triple
T6392750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Denny Crum |
E143867
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Denzel |
E221927
|
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: Denzel | Statement: [Denny Crum, givenName, Denzel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Denzel Context triple: [Denny Crum, givenName, Denzel]
-
A.
Denzel
chosen
Denzel is a masculine given name most famously associated with acclaimed American actor and filmmaker Denzel Washington.
-
B.
Terrence Howard
Terrence Howard is an American actor and singer known for his roles in films like "Hustle & Flow" and the TV series "Empire."
-
C.
Orlando Jones
Orlando Jones was an early 18th-century Virginia planter and colonial official connected to the prominent Jones and Dandridge families.
-
D.
Orlando Jones
Orlando Jones is an American actor and comedian known for his roles in television and film, including his prominent part in the supernatural drama series "Sleepy Hollow."
-
E.
Ving Rhames
Ving Rhames is an American actor best known for his deep voice and memorable roles in films such as the Mission: Impossible series and Pulp Fiction.
- 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_69c008db906c819096f3597d55d95432 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0687f5c6c81909c835329c996b311 |
completed | March 22, 2026, 10:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c640ba9e04819098713f5bea7ebdbc |
completed | March 27, 2026, 8:32 a.m. |
Created at: March 22, 2026, 4:34 p.m.