Triple
T29986166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brock Marion |
E761739
|
entity |
| Predicate | careerKickReturnYards |
P168725
|
FINISHED |
| Object | 1,524 |
—
|
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: 1,524 | Statement: [Brock Marion, careerKickReturnYards, 1,524]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: careerKickReturnYards Context triple: [Brock Marion, careerKickReturnYards, 1,524]
-
A.
careerPuntReturnYards
Indicates the total number of yards an entity has gained on punt returns over the course of their entire career.
-
B.
careerInterceptionReturnYards
Indicates the total number of yards a player has gained on interception returns over the course of their entire career.
-
C.
careerReceivingYards
Indicates the total number of yards a player has gained by receiving the ball over the course of their entire career.
-
D.
careerFumbleRecoveries
Indicates the total number of times an entity has recovered a fumble over the course of their entire career.
-
E.
careerRushingYards
Indicates the total number of rushing yards an entity has accumulated over the entire span of its career.
- 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_69f2246851148190b8e76206db94b105 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f67915bf008190b87d771e157bd3c8 |
completed | May 2, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69f673c4abec8190bc2379e66f4af0a9 |
completed | May 2, 2026, 9:59 p.m. |
| PDg | Predicate description generation | batch_69f674df80b08190adb7f7531083bbb1 |
completed | May 2, 2026, 10:04 p.m. |
Created at: April 29, 2026, 6:36 p.m.