Triple
T18074743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maryland Terrapins football |
E432525
|
entity |
| Predicate | bowlGameWins |
P76997
|
FINISHED |
| Object | 10+ |
—
|
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+ | Statement: [Maryland Terrapins football, bowlGameWins, 10+]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bowlGameWins Context triple: [Maryland Terrapins football, bowlGameWins, 10+]
-
A.
bowlGame
Indicates that the relationship or event involves a postseason college football bowl game in which a team participates or that is associated with an entity.
-
B.
hasWonBowlGames
chosen
Indicates that one entity has achieved victories in one or more bowl games associated with another entity.
-
C.
hasWonBowlGame
Indicates that a team or individual has achieved victory in a specific bowl game competition.
-
D.
numberOfBowlGamesPlayed
Indicates the total count of bowl games that an entity (typically a sports team or player) has participated in.
-
E.
SuperBowlWins
Indicates the number of Super Bowl championships that a team or individual has won.
- 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_69d8b9070cac81909fa9473fb1c3f1c7 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4d9f40c9881909294d538c026d486 |
completed | April 19, 2026, 1:34 p.m. |
| PD | Predicate disambiguation | batch_69e3f90c652481908133a73106d78919 |
completed | April 18, 2026, 9:35 p.m. |
Created at: April 10, 2026, 10:26 a.m.