Triple
T3964863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NCAA Division II Wrestling Championships |
E92190
|
entity |
| Predicate | weightClasses |
P8068
|
FINISHED |
| Object | multiple collegiate weight classes |
—
|
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: multiple collegiate weight classes | Statement: [NCAA Division II Wrestling Championships, weightClasses, multiple collegiate weight classes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: weightClasses Context triple: [NCAA Division II Wrestling Championships, weightClasses, multiple collegiate weight classes]
-
A.
weightClass
chosen
Indicates the categorical grouping of an entity based on its weight range or mass classification.
-
B.
speedClass
Indicates the categorical speed level or range assigned to an entity based on how fast it moves or operates.
-
C.
wearingClass
Indicates that one entity is wearing or dressed in an item belonging to a particular class or category of clothing or accessories.
-
D.
heightClass
Indicates the categorical height level or range to which an entity is assigned (e.g., short, medium, tall).
-
E.
competitionClass
Indicates that one entity is classified into a particular competitive category or level within a competition or contest.
- 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_69aed96624188190ac8c45bb57ab72b5 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefba878a48190a2e234d775215938 |
completed | March 9, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69aef8efcf3c81908ccf61d9ce26b0c0 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:31 p.m.