Triple
T10151603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ralph Miller |
E232654
|
entity |
| Predicate | genreOfCoachingStyle |
P29237
|
FINISHED |
| Object | disciplined half-court offense |
—
|
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: disciplined half-court offense | Statement: [Ralph Miller, genreOfCoachingStyle, disciplined half-court offense]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfCoachingStyle Context triple: [Ralph Miller, genreOfCoachingStyle, disciplined half-court offense]
-
A.
coachingTrait
chosen
Indicates that one entity possesses a characteristic, style, or quality specifically related to coaching.
-
B.
coachingSpecialty
Indicates that a coach focuses on or is specialized in a particular area, topic, or type of coaching.
-
C.
coachingRecordType
Indicates the specific category or nature of a coaching record associated with an entity or event.
-
D.
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.
-
E.
hasDecisionMakingStyle
Indicates that an entity possesses or exhibits a particular way or pattern of making decisions.
- 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_69ca84885e48819088a31b127cf44904 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cdec0584a48190b65daa8370555c27 |
completed | April 2, 2026, 4:09 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba4f5d88190ba68e63be10b08c7 |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:08 p.m.