Triple
T6017019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deacon Jones |
E133971
|
entity |
| Predicate | NFLDefensivePlayerOfTheYearCount |
P17671
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Deacon Jones, NFLDefensivePlayerOfTheYearCount, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: NFLDefensivePlayerOfTheYearCount Context triple: [Deacon Jones, NFLDefensivePlayerOfTheYearCount, 2]
-
A.
numberOfDefensivePlayerOfTheYearAwards
chosen
Indicates the count of times an entity has received the Defensive Player of the Year award.
-
B.
defensivePlayerOfTheYear
Indicates that the subject was recognized or awarded as the top defensive player of the year in a particular league, competition, or season.
-
C.
RavensDefensiveTouchdownPlayer
Indicates that a player on the Ravens scored a touchdown while the Ravens were on defense (e.g., via interception or fumble return).
-
D.
defensiveTackle
Indicates that an entity plays the defensive tackle position, typically lining up on the interior of the defensive line to disrupt offensive plays.
-
E.
nflCareerSacks
Indicates the number of times a defensive player has successfully tackled the opposing quarterback behind the line of scrimmage during their NFL career.
- F. None of above.
Provenance (3 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_69c0087361a48190905c6b55969852b8 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04f8458588190a78aa32cbdbecfb1 |
completed | March 22, 2026, 8:22 p.m. |
| PD | Predicate disambiguation | batch_69c049e75b3881908be106fbcf8c68d4 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:06 p.m.