Triple
T18231080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kyler Murray |
E436542
|
entity |
| Predicate | choseSportOver |
P130337
|
FINISHED |
| Object | chose NFL career over MLB career |
—
|
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: chose NFL career over MLB career | Statement: [Kyler Murray, choseSportOver, chose NFL career over MLB career]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: choseSportOver Context triple: [Kyler Murray, choseSportOver, chose NFL career over MLB career]
-
A.
usedSportFor
Indicates that an entity employs or utilizes a particular sport as a means, tool, or context for achieving some purpose or performing an activity.
-
B.
includesSport
Indicates that one entity contains, offers, or features a particular sport as part of its activities, content, or composition.
-
C.
sportCreatedAsAlternativeTo
Indicates that one sport was developed specifically to serve as a substitute or alternative to another sport.
-
D.
multiSport
Indicates that an entity participates in, is associated with, or is designed for more than one sport.
-
E.
primarySport
Indicates the main sport with which an entity (such as a person, team, or organization) is most closely associated or primarily involved.
- 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_69d8b9103a8081908bbb0836fef10efd |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4f4b3495881909f2a3f3a8db43792 |
completed | April 19, 2026, 3:28 p.m. |
| PD | Predicate disambiguation | batch_69e4332336cc8190808b9c70c888ba65 |
completed | April 19, 2026, 1:42 a.m. |
| PDg | Predicate description generation | batch_69e438f684e48190b38c64b58c518b6a |
completed | April 19, 2026, 2:07 a.m. |
Created at: April 10, 2026, 10:33 a.m.