Triple
T32077969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Andrews |
E819209
|
entity |
| Predicate | playsOffense |
P52799
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Mark Andrews, playsOffense, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: playsOffense Context triple: [Mark Andrews, playsOffense, true]
-
A.
playsRoleInOffense
Indicates that an entity performs a specific function or position within an offensive strategy or system.
-
B.
offensivePlayType
Indicates the specific type of offensive play that is being executed or has occurred within a game or sporting context.
-
C.
offensiveTackle
chosen
Indicates that an entity plays the offensive tackle position, responsible for blocking and protecting on the offensive line in a gridiron football context.
-
D.
offensiveCoordinator
Indicates that one entity serves as the offensive coordinator (the coach responsible for directing the offensive unit) for another entity, typically a sports team.
-
E.
playedAmericanFootball
Indicates that one entity participated in playing American football, either professionally, collegiately, or at another organized level, during some period of time.
- 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_69f348ff8ef88190931c08ba530a36bc |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f70e8755a48190931eaa77946f9460 |
completed | May 3, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f70abc00848190a1c3f495ef6c8dc6 |
completed | May 3, 2026, 8:43 a.m. |
Created at: May 1, 2026, 12:24 a.m.