Triple
T4009783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erik Spoelstra |
E90613
|
entity |
| Predicate | jerseyNumberInCollege |
P2651
|
FINISHED |
| Object | 30 |
—
|
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: 30 | Statement: [Erik Spoelstra, jerseyNumberInCollege, 30]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: jerseyNumberInCollege Context triple: [Erik Spoelstra, jerseyNumberInCollege, 30]
-
A.
retiredJerseyCollege
Indicates that a college has formally retired a particular jersey number, typically in honor of a former player or coach associated with that institution.
-
B.
jerseyNumber
chosen
Indicates the specific uniform number assigned to and worn by an individual, typically in a sports context.
-
C.
jerseyNumberCoached
Indicates that a coach was responsible for coaching a player (or players) who wore a specific jersey number.
-
D.
playedForCollegeTeamFrom
Indicates that an individual was a member of and played for a specific college team starting in a given year.
-
E.
positionPlayedInCollege
Indicates the specific playing position an individual held on a sports team during their college career.
- 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_69aed95e44088190aff7d90a151b1b20 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaec08dc8190a341809059554f84 |
completed | March 9, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69aef8fa6fec81909b1190ecbba61410 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:34 p.m.