Triple
T20238937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chris Lighty |
E498228
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Darrell |
—
|
NE NERFINISHED |
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: [Chris Lighty, givenName, Darrell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Darrell Context triple: [Chris Lighty, 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.
Darrell
chosen
Darrell is a masculine given name of English origin commonly used in the United States and other English-speaking countries.
-
C.
Derrel
Derrel is the given first name of former Major League Baseball shortstop and manager Bud Harrelson.
-
D.
Darell
Darell is a surname most notably associated with characters in Isaac Asimov’s Foundation series, including the psychohistorian Bayta Darell.
-
E.
Darell
Darell is a Puerto Rican reggaeton and Latin trap singer and rapper known for his collaborations on major urban Latin hits.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da6274c58c81909c646eabed6f4f30 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6716c8de88190916bfa1d6b7f79cb |
completed | April 20, 2026, 6:33 p.m. |
Created at: April 11, 2026, 11:40 p.m.