Triple
T5867162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naismith College Coach of the Year |
E130422
|
entity |
| Predicate | hasSeparateCategories |
P22702
|
FINISHED |
| Object | men’s award |
—
|
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: men’s award | Statement: [Naismith College Coach of the Year, hasSeparateCategories, men’s award]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeparateCategories Context triple: [Naismith College Coach of the Year, hasSeparateCategories, men’s award]
-
A.
hasSeparateSupportingCategory
chosen
Indicates that an entity is associated with an additional, distinct category used specifically for supporting or auxiliary classification purposes separate from its primary category.
-
B.
hasCategoryCount
Indicates the number of distinct categories associated with a given entity.
-
C.
hasCategoryOn
Indicates that something is assigned to or associated with a specific category within a given context or scope.
-
D.
hasSpecialCategory
Indicates that an entity is associated with a designated special or exceptional category distinct from its standard classifications.
-
E.
hasRelatedCategory
Indicates that one category is associated with another category through a non-hierarchical, contextually relevant relationship.
- 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_69c0085047dc8190af24e311edad3c07 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ffaef081909faaa7f420a3b9b7 |
completed | March 22, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69c03347e51c81909053bcf34e3b88ab |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:56 p.m.