Triple
T22995151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mike Budenholzer |
E572167
|
entity |
| Predicate | yearsWithSanAntonioSpursStaff |
P40869
|
FINISHED |
| Object | approximately 1994–2013 |
—
|
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: approximately 1994–2013 | Statement: [Mike Budenholzer, yearsWithSanAntonioSpursStaff, approximately 1994–2013]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearsWithSanAntonioSpursStaff Context triple: [Mike Budenholzer, yearsWithSanAntonioSpursStaff, approximately 1994–2013]
-
A.
NBAteamTenure
Indicates the period of time during which a player is a member of a specific NBA team.
-
B.
yearsWithTeam
chosen
Indicates the number of years an entity (typically a person) has been associated with or part of a particular team.
-
C.
teamStartYear
Indicates the year in which an entity (such as a person or organization) began its association with a particular team.
-
D.
careerSpanTeam
Indicates the team for which an individual’s entire career span (or a defined portion of it) is being measured or associated.
-
E.
coachOfYearTeam
Indicates that a person who received a coach of the year honor did so while coaching the specified 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_69e245b535808190adef8a9df3c584db |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f182f25af48190a98b7baeec824ae6 |
completed | April 29, 2026, 4:02 a.m. |
| PD | Predicate disambiguation | batch_69ef3b974e7c8190b8be11dbb4518693 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:50 p.m.