Triple
T35833035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mel Blount rule |
E1035850
|
entity |
| Predicate | penaltyResult |
P184203
|
FINISHED |
| Object | automatic first down |
—
|
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: automatic first down | Statement: [Mel Blount rule, penaltyResult, automatic first down]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: penaltyResult Context triple: [Mel Blount rule, penaltyResult, automatic first down]
-
A.
penaltyStatus
Indicates the current state or condition of a penalty that has been assigned or is applicable in a given context.
-
B.
finalScorePenalties
Indicates the penalties that are applied to determine or adjust the final score in a given context.
-
C.
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.
-
D.
penaltyOrder
Indicates that an authority has issued a formal decision imposing a penalty or sanction on a party.
-
E.
penaltyAppliesTo
Indicates that a specific penalty is imposed on, or is relevant to, a particular entity or situation.
- 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_69f7acaec1508190a38f2ac9cc5383e7 |
completed | May 3, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f7ab734d848190a84f9b8c3a952b75 |
completed | May 3, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69f7ac2210e481909279dade5328825c |
completed | May 3, 2026, 8:12 p.m. |
Created at: May 3, 2026, 4:06 p.m.