Triple
T21244124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Owens |
E523557
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | Terrell Owens |
—
|
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: Terrell Owens | Statement: [Owens, hasNotableBearer, Terrell Owens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Terrell Owens Context triple: [Owens, hasNotableBearer, Terrell Owens]
-
A.
Terrell Owens
chosen
Terrell Owens is a former American football wide receiver and Pro Football Hall of Famer known for his prolific receiving stats and flamboyant on-field celebrations in the NFL.
-
B.
Darren Evans
Darren Evans is a Welsh actor known for his roles in gritty historical and crime dramas on television and film.
-
C.
Terry Crabtree
Terry Crabtree is a flamboyant, free-spirited book editor and friend of the protagonist in Michael Chabon’s novel (and its film adaptation) "Wonder Boys."
-
D.
Ty Law
Ty Law is a former NFL cornerback best known for his Pro Bowl career with the New England Patriots and induction into the Pro Football Hall of Fame.
-
E.
Tim Jeffery
Tim Jeffery is a musician known for his involvement with the act Happiness.
- 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_69e0b513b89c81908b27147e91368db2 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7352621488190bd74c57798c7d658 |
completed | April 21, 2026, 8:28 a.m. |
Created at: April 16, 2026, 3:47 p.m.