Triple
T1564521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Geno Auriemma |
E33401
|
entity |
| Predicate | coachingLevel |
P26832
|
FINISHED |
| Object | college basketball |
—
|
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: college basketball | Statement: [Geno Auriemma, coachingLevel, college basketball]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coachingLevel Context triple: [Geno Auriemma, coachingLevel, college basketball]
-
A.
coachesLevel
chosen
Indicates the level or tier at which one entity coaches another, such as their rank, division, or proficiency category in a coaching context.
-
B.
trainingLevel
Indicates the degree or stage of training or skill development that an entity has attained.
-
C.
coachingSpecialty
Indicates that a coach focuses on or is specialized in a particular area, topic, or type of coaching.
-
D.
achievementLevel
Indicates the degree or extent to which an entity has attained a particular goal, standard, or performance outcome.
-
E.
positionCoached
Indicates that one entity served as a coach for another entity in a specific position or role.
- 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_69a885f11b048190935025a035302715 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90fccd4b48190a44012888a00af7f |
completed | March 5, 2026, 5:08 a.m. |
| PD | Predicate disambiguation | batch_69a907b872f0819096b3df6ad502c63e |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:27 p.m.