Triple
T7102582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eddie George |
E165492
|
entity |
| Predicate | nflRushingYardsCareer |
P14715
|
FINISHED |
| Object | 10000+ |
—
|
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: 10000+ | Statement: [Eddie George, nflRushingYardsCareer, 10000+]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nflRushingYardsCareer Context triple: [Eddie George, nflRushingYardsCareer, 10000+]
-
A.
NFLAllTimeRushingYardsLeader
Indicates that the subject is the player who has accumulated the most career rushing yards in NFL history.
-
B.
careerRushingYards
chosen
Indicates the total number of rushing yards an entity has accumulated over the entire span of its career.
-
C.
nflRushingYardsLeader
Indicates the player who gained the most rushing yards in the NFL over a specified season or time period.
-
D.
nflRushingTouchdownsLeader
Indicates the player who led all others in the number of rushing touchdowns in a given NFL season or context.
-
E.
careerReceivingYards
Indicates the total number of yards a player has gained by receiving the ball 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_69c6887fcddc8190a5d58908f6dee590 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e588aee08190bfb3d96135c0a322 |
completed | March 27, 2026, 8:16 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c313e481908b61a23fc89f9332 |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:42 p.m.