Triple
T3797197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marc Bulger |
E91599
|
entity |
| Predicate | woreNumberForTeam |
P2651
|
FINISHED |
| Object | 10 for St. Louis Rams |
—
|
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: 10 for St. Louis Rams | Statement: [Marc Bulger, woreNumberForTeam, 10 for St. Louis Rams]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: woreNumberForTeam Context triple: [Marc Bulger, woreNumberForTeam, 10 for St. Louis Rams]
-
A.
jerseyNumber
chosen
Indicates the specific uniform number assigned to and worn by an individual, typically in a sports context.
-
B.
wearsJerseyFor
Indicates that one entity wears a jersey representing, belonging to, or in support of another entity (such as a team, organization, or individual).
-
C.
jerseyNumberCoached
Indicates that a coach was responsible for coaching a player (or players) who wore a specific jersey number.
-
D.
leagueRetiredNumberBy
Indicates that a sports league has officially retired a specific jersey number in honor of a particular person or entity.
-
E.
namedForTeam
Indicates that one entity has been given its name in honor of, or derived from, a particular 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_69aed96354f48190a768966d6bd19b04 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeecefa3608190a7a20ed6df6a64b2 |
completed | March 9, 2026, 3:53 p.m. |
| PD | Predicate disambiguation | batch_69aee743c8d08190a9f9c97b836bd703 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:15 p.m.