Triple
T24701323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Nathaniel Brown |
E611749
|
entity |
| Predicate | careerYardsFromScrimmage |
P91386
|
FINISHED |
| Object | 15349 |
—
|
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: 15349 | Statement: [James Nathaniel Brown, careerYardsFromScrimmage, 15349]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: careerYardsFromScrimmage Context triple: [James Nathaniel Brown, careerYardsFromScrimmage, 15349]
-
A.
totalYardsFromScrimmageInSeason
Indicates the total number of yards a player gained from scrimmage (both rushing and receiving) over the course of a single season.
-
B.
yardsFromScrimmageCareerNFL
chosen
Indicates the total number of yards a player has gained from scrimmage over their entire NFL career.
-
C.
careerYardsPerCarry
Indicates the average number of yards a player gains per rushing attempt over the entirety of their career.
-
D.
careerReceivingYards
Indicates the total number of yards a player has gained by receiving the ball over the course of their entire career.
-
E.
careerPuntReturnYards
Indicates the total number of yards an entity has gained on punt returns 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_69e2c4d76d148190b58ad612467149a5 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f422aee0408190899efe7e24ef2b40 |
completed | May 1, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69f420e92cc88190a803aecdae78a051 |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 3:22 a.m.