Triple
T5949991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reggie White |
E132371
|
entity |
| Predicate | careerSacksNFL |
P41411
|
FINISHED |
| Object | 198 |
—
|
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: 198 | Statement: [Reggie White, careerSacksNFL, 198]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: careerSacksNFL Context triple: [Reggie White, careerSacksNFL, 198]
-
A.
joinedNFL
Indicates that an entity became a member of, or started playing in, the National Football League (NFL).
-
B.
careerReceivingTouchdowns
Indicates the total number of touchdowns a player has scored by receiving the ball over the course of their entire career.
-
C.
careerOPS
Indicates a relationship where an entity’s career on-base plus slugging (OPS) statistic is recorded or associated with that entity.
-
D.
careerFumbleRecoveries
Indicates the total number of times an entity has recovered a fumble over the course of their entire career.
-
E.
careerSacks
chosen
Indicates the total number of times a defensive player has sacked a quarterback over the course of their entire 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_69c00869d3308190af89b2453e0f7546 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c03ee10b308190afe38b904ae7c5f7 |
completed | March 22, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69c0335806788190b6488ca8b73f7a63 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 4:02 p.m.