Triple
T6493328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenny Dillingham |
E148093
|
entity |
| Predicate | roleAtAuburn |
P38510
|
FINISHED |
| Object | offensive coordinator |
—
|
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: offensive coordinator | Statement: [Kenny Dillingham, roleAtAuburn, offensive coordinator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleAtAuburn Context triple: [Kenny Dillingham, roleAtAuburn, offensive coordinator]
-
A.
roleAtInstitution
chosen
Indicates that an entity holds or has held a specific role or position within a particular institution.
-
B.
campusRole
Indicates the specific position, function, or capacity an individual holds within a campus or academic institution.
-
C.
notableStudentBodyAssociatedWith
Indicates that there is a significant or noteworthy group of students associated with a particular entity, such as an institution, organization, or program.
-
D.
hadAlumniRole
Indicates that an entity previously held a role or position as an alumnus/alumna of another entity (such as an institution or organization).
-
E.
roleAtD.C.United
Indicates that an entity holds or held a specific role or position within the D.C. United soccer organization.
- 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_69c009088f3081909cd467b05919de30 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06ab6abbc8190a4971ad5a654b0cd |
completed | March 22, 2026, 10:18 p.m. |
| PD | Predicate disambiguation | batch_69c06740bebc81909d9d6956baa2bcb9 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:53 p.m.