Triple
T35833034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mel Blount rule |
E1035850
|
entity |
| Predicate | penaltyYardage |
P184171
|
FINISHED |
| Object | 5 yards |
—
|
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: 5 yards | Statement: [Mel Blount rule, penaltyYardage, 5 yards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: penaltyYardage Context triple: [Mel Blount rule, penaltyYardage, 5 yards]
-
A.
penaltyScoredBy
Indicates that a penalty (typically in a game or sport) was successfully converted or scored by a particular participant.
-
B.
penaltyPoints
Indicates that a certain number of negative points or demerits are assigned to an entity as a consequence of a rule violation, error, or infraction.
-
C.
penaltyMinute
Indicates that a player is assessed a specific number of penalty minutes, typically for an infraction in a timed sporting event.
-
D.
penaltyAwardedToTeam
Indicates that a penalty has been given in favor of a specific team.
-
E.
finalScorePenalties
Indicates the penalties that are applied to determine or adjust the final score in a given context.
- F. None of above. chosen
Provenance (4 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_69f76e192a94819082db360cb91e6a8d |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7aaabb58c8190bf81673608ecfb6e |
completed | May 3, 2026, 8:06 p.m. |
| PD | Predicate disambiguation | batch_69f7a8d219f8819081dc4ce3c83ca0cb |
completed | May 3, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f7aa6795f481908940838ee7041ff5 |
completed | May 3, 2026, 8:04 p.m. |
Created at: May 3, 2026, 4:06 p.m.