Triple
T7975188
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jim Plunkett |
E185425
|
entity |
| Predicate | NFLTouchdownPasses |
P80105
|
FINISHED |
| Object | 164 |
—
|
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: 164 | Statement: [Jim Plunkett, NFLTouchdownPasses, 164]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: NFLTouchdownPasses Context triple: [Jim Plunkett, NFLTouchdownPasses, 164]
-
A.
ledNFLInPassingTouchdowns
Indicates that the subject was the league leader in passing touchdowns in the NFL for a given season or time period.
-
B.
touchdownsScored
Indicates the number of touchdowns that an entity has scored.
-
C.
careerNFLTouchdowns
Indicates the total number of touchdowns a player has scored over the course of their NFL career.
-
D.
gameWinningTouchdownPasser
Indicates that the subject is the player who threw the touchdown pass that secured the victory in the game for the subject's team.
-
E.
nflRecord
Indicates the win-loss-tie performance record a team or individual has accumulated in NFL competition.
- 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_69ca829851908190b4e03829353ee7c3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3bf42a508190bb661fce34ec0151 |
completed | March 31, 2026, 3:13 a.m. |
| PD | Predicate disambiguation | batch_69cb047a8e4c81909b79e0f0bf56440c |
completed | March 30, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69cb14bbbacc81909c6cf8ec35314bbb |
completed | March 31, 2026, 12:26 a.m. |
Created at: March 30, 2026, 5:14 p.m.