Triple
T36134361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1971 Nebraska vs. Oklahoma football game |
E1045119
|
entity |
| Predicate | JohnnyRodgersPuntReturnDistance |
P184740
|
FINISHED |
| Object | 72 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: 72 yards | Statement: [1971 Nebraska vs. Oklahoma football game, JohnnyRodgersPuntReturnDistance, 72 yards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: JohnnyRodgersPuntReturnDistance Context triple: [1971 Nebraska vs. Oklahoma football game, JohnnyRodgersPuntReturnDistance, 72 yards]
-
A.
interceptionReturnYards
Indicates the number of yards gained by a defensive player while returning an intercepted pass.
-
B.
careerKickReturnYards
Indicates the total number of yards a player has gained on kickoff returns over the course of their entire career.
-
C.
careerPuntReturnYards
Indicates the total number of yards an entity has gained on punt returns over the course of their entire career.
-
D.
hasNFLRushingTouchdowns
Indicates that an entity (typically a player or team) has scored one or more rushing touchdowns in NFL games.
-
E.
gameWinningFieldGoalDistance
Indicates the distance from which a decisive, game-winning field goal was successfully kicked.
- 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_69f76e36a4508190b5bfc8f594272a4c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b3e2f3c08190be4fd1ae4fa1266d |
completed | May 3, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bcc47081909fe7d592ac69006c |
completed | May 3, 2026, 8:36 p.m. |
| PDg | Predicate description generation | batch_69f7b3e0f1c88190985feab6cee8b05e |
completed | May 3, 2026, 8:45 p.m. |
Created at: May 3, 2026, 4:08 p.m.