Triple
T19997338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nykesha Sales |
E494227
|
entity |
| Predicate | hasPlayedProfessionalBasketball |
P64063
|
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: [Nykesha Sales, hasPlayedProfessionalBasketball, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlayedProfessionalBasketball Context triple: [Nykesha Sales, hasPlayedProfessionalBasketball, true]
-
A.
playedInNBA
Indicates that the subject has participated as a player in at least one official National Basketball Association (NBA) game.
-
B.
playedBasketballFor
Indicates that one entity was a member of and competed for another entity’s basketball team.
-
C.
hasPlayedProfessionalSports
chosen
Indicates that an entity has participated as an athlete in an officially recognized professional-level sports competition or league.
-
D.
hasBasketballLevel
Indicates that an entity possesses a specified level of skill, proficiency, or ranking in basketball.
-
E.
playedCollegeBasketballFor
Indicates that a person was a member of and competed for a specific college or university’s basketball team.
- 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_69da626b2d748190886981ea90c8b2ea |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65fe549108190947a4d1a587c08f8 |
completed | April 20, 2026, 5:18 p.m. |
| PD | Predicate disambiguation | batch_69e537fd311881908448f2aea8b4812e |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 11, 2026, 3:32 p.m.