Triple
T7616216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Shaw |
E172366
|
entity |
| Predicate | genreOfCoaching |
P13768
|
FINISHED |
| Object | offensive 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: offensive football | Statement: [David Shaw, genreOfCoaching, offensive football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfCoaching Context triple: [David Shaw, genreOfCoaching, offensive football]
-
A.
coachingSpecialty
chosen
Indicates that a coach focuses on or is specialized in a particular area, topic, or type of coaching.
-
B.
coachingRecordType
Indicates the specific category or nature of a coaching record associated with an entity or event.
-
C.
movementCoach
Indicates a relationship where one entity serves as a coach or instructor guiding another entity’s physical movement or movement-related skills.
-
D.
coachingTrait
Indicates that one entity possesses a characteristic, style, or quality specifically related to coaching.
-
E.
usesCoachType
Indicates that an entity employs or operates a specific type or category of coach (e.g., vehicle or carriage) in its service or context.
- 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_69c6994f50808190ba228764bb422417 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6fe73ff7c8190ab1218d97b37416d |
completed | March 27, 2026, 10:02 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e725a88190b1f05dd224f7f4f2 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:55 p.m.