Triple
T3071455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adam Vinatieri |
E64031
|
entity |
| Predicate | nflRecord |
P44267
|
FINISHED |
| Object | most career points scored |
—
|
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: most career points scored | Statement: [Adam Vinatieri, nflRecord, most career points scored]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nflRecord Context triple: [Adam Vinatieri, nflRecord, most career points scored]
-
A.
coachingRecordNFLWins
Indicates the number of NFL games a coach has won in their coaching career.
-
B.
coachingRecordNFLTies
Indicates the number of tied games on an NFL coach’s professional coaching record.
-
C.
NFCChampionRecord
Indicates that a team holds a record related to winning or appearing in NFC Championship games.
-
D.
ledNFLInPassingTouchdowns
Indicates that the subject was the league leader in passing touchdowns in the NFL for a given season or time period.
-
E.
finalNflSeason
Indicates that the referenced season is the last NFL season in which the entity (typically a player, coach, or team configuration) participated or was active.
- 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_69ad857a8aec8190bfdfd9c14554ac5a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada14b366881908e2ca104e5f38251 |
completed | March 8, 2026, 4:18 p.m. |
| PD | Predicate disambiguation | batch_69ad9625b30c819099ef9349c91d7b25 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97f7630c81908e1ca8a69611cff6 |
completed | March 8, 2026, 3:38 p.m. |
Created at: March 8, 2026, 3:02 p.m.