Triple
T16446653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saquon Barkley |
E399446
|
entity |
| Predicate | playsOffensiveUnit |
P78138
|
FINISHED |
| Object | offense |
—
|
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: offense | Statement: [Saquon Barkley, playsOffensiveUnit, offense]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: playsOffensiveUnit Context triple: [Saquon Barkley, playsOffensiveUnit, offense]
-
A.
offensiveForce
Indicates the use or application of aggressive or attacking power or violence by one entity against another.
-
B.
offensiveStrategy
Indicates a strategic approach focused on attacking or aggressively advancing against an opponent.
-
C.
playsRoleInOffense
chosen
Indicates that an entity performs a specific function or position within an offensive strategy or system.
-
D.
offensiveStrength
Indicates the degree or capacity of an entity to carry out effective attacks or aggressive actions against an opponent.
-
E.
offensiveTackle
Indicates that an entity plays the offensive tackle position, responsible for blocking and protecting on the offensive line in a gridiron football context.
- 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_69d87f2c6778819080fcfae53be8f12a |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32cdcedf8819080aa82a8712c0b42 |
completed | April 18, 2026, 7:03 a.m. |
| PD | Predicate disambiguation | batch_69e227048d608190a4205eae3117629a |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:10 a.m.