Triple
T19627751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chris Long |
E471181
|
entity |
| Predicate | jerseyNumberCollege |
P2651
|
FINISHED |
| Object | 91 |
—
|
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: 91 | Statement: [Chris Long, jerseyNumberCollege, 91]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: jerseyNumberCollege Context triple: [Chris Long, jerseyNumberCollege, 91]
-
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.
jerseyNumberTeam
Indicates the association between a specific jersey number and the team for which that jersey number is used or assigned.
-
C.
jerseyNumber
chosen
Indicates the specific uniform number assigned to and worn by an individual, typically in a sports context.
-
D.
jerseyNumberCoached
Indicates that a coach was responsible for coaching a player (or players) who wore a specific jersey number.
-
E.
playedForCollegeTeamFrom
Indicates that an individual was a member of and played for a specific college team starting in a given year.
- 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_69d8e511f28481909f4bc3ea9191e54a |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e640eadcc48190ab5e36ddcde0c328 |
completed | April 20, 2026, 3:06 p.m. |
| PD | Predicate disambiguation | batch_69e514e5cb108190ae260e466c447314 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:44 p.m.