Triple
T15561637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jordyn Wieber |
E371013
|
entity |
| Predicate | roleAtCollegeTeam |
P13665
|
FINISHED |
| Object | volunteer assistant coach for UCLA gymnastics |
—
|
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: volunteer assistant coach for UCLA gymnastics | Statement: [Jordyn Wieber, roleAtCollegeTeam, volunteer assistant coach for UCLA gymnastics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleAtCollegeTeam Context triple: [Jordyn Wieber, roleAtCollegeTeam, volunteer assistant coach for UCLA gymnastics]
-
A.
roleAtSportsTeam
chosen
Indicates the specific position or function an individual holds within a sports team.
-
B.
collegeTeammateOf
Indicates that two individuals were teammates on the same college sports team.
-
C.
workedForCollegeTeam
Indicates that an individual was employed by or served in a working role for a college sports team.
-
D.
roleInClub
Indicates that an entity holds a specific position or function within a particular club.
-
E.
memberTeam
Indicates that an entity belongs to or is part of a specific 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_69d85cc6cf40819091f4a5facee1ebe6 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ddb4c0c81909b3f4c75c91f7f3f |
completed | April 16, 2026, 2:47 a.m. |
| PD | Predicate disambiguation | batch_69deda7e6e748190b29ccce23298afef |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:09 a.m.