Triple
T17716693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duquesne Dukes football |
E442217
|
entity |
| Predicate | playedLevel |
P39395
|
FINISHED |
| Object | major college football in the 1930s |
—
|
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: major college football in the 1930s | Statement: [Duquesne Dukes football, playedLevel, major college football in the 1930s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: playedLevel Context triple: [Duquesne Dukes football, playedLevel, major college football in the 1930s]
-
A.
playedAtLevel
chosen
Indicates that an entity participated or performed in an activity, event, or game at a specified level of difficulty, competition, or hierarchy.
-
B.
playedUntil
Indicates that an action or event involving playing continued up to a specific time, point, or condition.
-
C.
achievementLevel
Indicates the degree or extent to which an entity has attained a particular goal, standard, or performance outcome.
-
D.
playedCode
Indicates that an entity performed or executed a specific piece of code.
-
E.
intendedPlayerLevel
Indicates the player level for which something (such as content, an item, or a challenge) is designed or meant to be used.
- 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_69d8b9ec79688190b86bdcef85a7b3aa |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e47481663c8190a1110385e5596ab0 |
completed | April 19, 2026, 6:21 a.m. |
| PD | Predicate disambiguation | batch_69e3cde601d4819097903f471f1fe99a |
completed | April 18, 2026, 6:31 p.m. |
Created at: April 10, 2026, 10:06 a.m.