Triple
T6493329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenny Dillingham |
E148093
|
entity |
| Predicate | roleAtMemphis |
P71050
|
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, roleAtMemphis, offensive coordinator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleAtMemphis Context triple: [Kenny Dillingham, roleAtMemphis, offensive coordinator]
-
A.
hasCityRole
Indicates that an entity holds or is assigned a specific role, function, or status within a particular city.
-
B.
roleInFranchiseHistory
Indicates the specific function, position, or contribution an entity has within the historical development or timeline of a franchise.
-
C.
roleInManchesterCity
Indicates that an entity holds or has held a specific role or position within Manchester City Football Club.
-
D.
roleAsPlace
Indicates that an entity functions or is used as a place or location in relation to another entity or event.
-
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. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69c067f1ef148190bc0355abe83f7e16 |
completed | March 22, 2026, 10:06 p.m. |
Created at: March 22, 2026, 4:53 p.m.