Triple
T16515272
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alabama Stakes |
E401165
|
entity |
| Predicate | typicalWeightAssignment |
P1335
|
FINISHED |
| Object | assigned weights for age |
—
|
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: assigned weights for age | Statement: [Alabama Stakes, typicalWeightAssignment, assigned weights for age]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalWeightAssignment Context triple: [Alabama Stakes, typicalWeightAssignment, assigned weights for age]
-
A.
weightingMethod
Indicates how relative importance or influence is assigned to elements within a set, such as criteria, features, or data points, in a calculation or decision process.
-
B.
averageWeight
chosen
Indicates the typical or mean weight value associated with an entity or group of entities.
-
C.
weightStandardInfluencedBy
Indicates that a weight standard is affected, shaped, or determined by another factor, standard, or influence.
-
D.
allowsWeightClasses
Indicates that one entity permits or supports the use of defined weight categories for another entity or within a given context.
-
E.
weightingFunction
Indicates a function that assigns relative importance or influence (weights) to elements within a set, often to adjust their impact in a calculation or decision process.
- 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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e7bbfa481909037148cdb4d8996 |
completed | April 18, 2026, 7:10 a.m. |
| PD | Predicate disambiguation | batch_69e296995d388190b88ebe189dce890d |
completed | April 17, 2026, 8:22 p.m. |
Created at: April 10, 2026, 5:14 a.m.