Triple
T5508181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kurt Rambis |
E144495
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Darrell |
E242538
|
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: Darrell | Statement: [Kurt Rambis, givenName, Darrell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Darrell Context triple: [Kurt Rambis, givenName, Darrell]
-
A.
Darrell
Darrell is the central protagonist of the film "In the Mix," around whom the story’s main events and conflicts revolve.
-
B.
Darryl
Darryl is a masculine given name most notably associated with influential American film producer and studio executive Darryl F. Zanuck.
-
C.
Darren
Darren is a masculine given name commonly used in English-speaking countries.
-
D.
Darren
Darren is a fictional continent located on the planet Skaro in the Doctor Who universe.
-
E.
Daryl
chosen
Daryl is a given name commonly used for people of any gender, notably borne by figures in sports, entertainment, and public life.
- 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_69c008f6b5048190a09064116062cf69 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f495c588190b0cfe5bfb3d2c221 |
completed | March 22, 2026, 4:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c027c082108190a3c8f826a6aeef4c |
completed | March 22, 2026, 5:32 p.m. |
Created at: March 22, 2026, 3:33 p.m.