Triple
T35885790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan Henderson vs Michael Bisping |
E1037638
|
entity |
| Predicate | HendersonNationality |
P78054
|
FINISHED |
| Object | United States |
—
|
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: United States | Statement: [Dan Henderson vs Michael Bisping, HendersonNationality, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: HendersonNationality Context triple: [Dan Henderson vs Michael Bisping, HendersonNationality, United States]
-
A.
nationalityOfPersonReferredTo
chosen
Indicates that one entity is the country or nationality associated with the person referenced by the other entity.
-
B.
honorsPersonNationality
Indicates that an entity honors, recognizes, or pays tribute to a person specifically in relation to that person's nationality.
-
C.
ownerNationality
Indicates that the owner of an entity has the specified nationality.
-
D.
AlexanderNationality
Indicates that an entity’s nationality is Alexander’s (i.e., that the entity is identified as belonging to the nation associated with Alexander).
-
E.
nationalityInHumanWorld
Indicates that one entity has the specified national affiliation or citizenship within the context of the human world.
- F. None of above.
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_69f76e1f4d748190bb55594d8441d70e |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7ac23d1388190bdf9628b294943bd |
completed | May 3, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f7ab734d848190a84f9b8c3a952b75 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4:06 p.m.