Triple
T28806501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luke Rodgers |
E727388
|
entity |
| Predicate | sportsDomainCovered |
P6214
|
FINISHED |
| Object | American football |
—
|
LITERAL 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: American football | Statement: [Luke Rodgers, sportsDomainCovered, American football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sportsDomainCovered Context triple: [Luke Rodgers, sportsDomainCovered, American football]
-
A.
sportingDomain
Indicates that one entity is the sport or sporting field in which the other entity participates, competes, or is primarily involved.
-
B.
otherSportsCovered
Indicates that additional sports, beyond a primary or main sport, are also included or reported on.
-
C.
sportsCategory
Indicates that one entity is classified as a type or category within the domain of sports to which the other entity belongs.
-
D.
sportFocus
chosen
Indicates that one entity has a primary emphasis, specialization, or concentration on a particular sport represented by the other entity.
-
E.
sportCategory
Indicates that one entity is classified as a type or category of sport to which the other entity (typically a specific sport or sporting event) belongs.
- 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_69f0319c38948190bca746ad60fd25ba |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f676f968d08190a4adba0439b438c9 |
completed | May 2, 2026, 10:13 p.m. |
| PD | Predicate disambiguation | batch_69f675ff62c48190a634bbb8896973b9 |
completed | May 2, 2026, 10:09 p.m. |
Created at: April 28, 2026, 6:29 a.m.