Triple
T1502387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pro Bowl |
E33822
|
entity |
| Predicate | ruleVariations |
P24476
|
FINISHED |
| Object | modified NFL rules to reduce injury risk |
—
|
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: modified NFL rules to reduce injury risk | Statement: [Pro Bowl, ruleVariations, modified NFL rules to reduce injury risk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ruleVariations Context triple: [Pro Bowl, ruleVariations, modified NFL rules to reduce injury risk]
-
A.
typicalRuleModification
chosen
Indicates a change made to a standard or default rule, adjusting how that rule normally applies or operates.
-
B.
usageVariesBy
Indicates that the way something is used differs depending on a specified factor, such as context, user, location, or conditions.
-
C.
hasVariability
Indicates that an entity exhibits variation or fluctuation in its state, value, or characteristics over time or across instances.
-
D.
affectsVariant
Indicates that one entity has an influence or impact on a specific variant or version of another entity.
-
E.
viewVariesAmong
Indicates that the way something is viewed, perceived, or interpreted differs across multiple entities or contexts.
- 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_69a885f352a4819099b24ff15489dede |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90584b8b881908e112c7e59163812 |
completed | March 5, 2026, 4:24 a.m. |
| PD | Predicate disambiguation | batch_69a88727ce48819089b482cdc25453d1 |
completed | March 4, 2026, 7:25 p.m. |
Created at: March 4, 2026, 7:24 p.m.