Triple
T17320445
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University Challenge |
E420544
|
entity |
| Predicate | questionStyle |
P126962
|
FINISHED |
| Object | toss-up and bonus format |
—
|
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: toss-up and bonus format | Statement: [University Challenge, questionStyle, toss-up and bonus format]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: questionStyle Context triple: [University Challenge, questionStyle, toss-up and bonus format]
-
A.
questionType
Indicates the specific category or kind of question that an item, query, or prompt belongs to.
-
B.
questionText
Indicates the textual content of a question as it is posed or displayed.
-
C.
questionPresented
Indicates that a question has been posed or displayed to an entity for consideration or response.
-
D.
questionForm
Indicates that one entity is expressed or structured in the form of a question directed toward another entity or context.
-
E.
questionStructure
Indicates the structural or grammatical arrangement that defines how a question is formed or organized.
- 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_69d889d22b848190a4663d0b8f8f76e7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e439a066b481908e8aee1885809eba |
completed | April 19, 2026, 2:10 a.m. |
| PD | Predicate disambiguation | batch_69e3b01b9d1c8190a406dd941c9b11a1 |
completed | April 18, 2026, 4:23 p.m. |
| PDg | Predicate description generation | batch_69e3b2a225b08190a50f984caa6513b9 |
completed | April 18, 2026, 4:34 p.m. |
Created at: April 10, 2026, 5:43 a.m.