Triple
T686296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cotton Bowl Classic |
E13290
|
entity |
| Predicate | inceptionSeason |
P18225
|
FINISHED |
| Object | 1937–38 bowl season |
—
|
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: 1937–38 bowl season | Statement: [Cotton Bowl Classic, inceptionSeason, 1937–38 bowl season]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inceptionSeason Context triple: [Cotton Bowl Classic, inceptionSeason, 1937–38 bowl season]
-
A.
inception
Indicates the point in time or event at which something begins, originates, or is first established.
-
B.
inceptionTime
Indicates the specific point in time when an entity, event, or relationship begins or is first established.
-
C.
hasSequel
Indicates that one work is followed by another work that continues its story, timeline, or thematic development.
-
D.
hasSequelNumber
Indicates that an entity is followed by another work in a series identified by a specific sequential number.
-
E.
numberOfSeasons
Indicates the total count of seasons associated with a particular entity (such as a series, competition, or event).
- F. None of above. chosen
Provenance (4 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_69a4933e0f98819097d22766c49b61b8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a0f55f7481909e052a25bd12d455 |
completed | March 1, 2026, 8:26 p.m. |
| PD | Predicate disambiguation | batch_69a49d2048d48190ab99ab59accb6909 |
completed | March 1, 2026, 8:10 p.m. |
| PDg | Predicate description generation | batch_69a4a0f405748190ba72a9cfe946a8ec |
completed | March 1, 2026, 8:26 p.m. |
Created at: March 1, 2026, 7:36 p.m.