Triple
T2299741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Markelle Fultz |
E51700
|
entity |
| Predicate | scoredPointsPerGameInCollege |
P38590
|
FINISHED |
| Object | 23.2 |
—
|
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: 23.2 | Statement: [Markelle Fultz, scoredPointsPerGameInCollege, 23.2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scoredPointsPerGameInCollege Context triple: [Markelle Fultz, scoredPointsPerGameInCollege, 23.2]
-
A.
positionPlayedInCollege
Indicates the specific playing position an individual held on a sports team during their college career.
-
B.
playedCollegeBasketballFor
Indicates that a person was a member of and competed for a specific college or university’s basketball team.
-
C.
playedCollegeSport
Indicates that the subject participated in an organized college-level sport for the object institution.
-
D.
playedCollegeTeam
Indicates that an athlete was a member of and competed for a particular college sports team.
-
E.
conferencePlayedInCollege
Indicates that a person participated in collegiate athletics within a specific athletic conference.
- 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_69a88b0a9f248190bcff941463d8f65a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abcbabf01081908db3b42bc7c60444 |
completed | March 7, 2026, 6:54 a.m. |
| PD | Predicate disambiguation | batch_69abc58ad33c8190b8d68af41b6f5e07 |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abcbab15488190bc8d2345f9d9f2bd |
completed | March 7, 2026, 6:54 a.m. |
Created at: March 4, 2026, 7:49 p.m.