Triple
T34040790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Chase: Celebrity Specials |
E872936
|
entity |
| Predicate | questionCategory |
P12351
|
FINISHED |
| Object | general knowledge |
—
|
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: general knowledge | Statement: [The Chase: Celebrity Specials, questionCategory, general knowledge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: questionCategory Context triple: [The Chase: Celebrity Specials, questionCategory, general knowledge]
-
A.
questionTopic
Indicates that a question is about, concerns, or is primarily focused on a particular topic or subject.
-
B.
questionType
chosen
Indicates the specific category or kind of question that an item, query, or prompt belongs to.
-
C.
questionText
Indicates the textual content of a question as it is posed or displayed.
-
D.
typicalQuestion
Indicates that an entity is a common or standard question typically asked in a given context or situation.
-
E.
questionPresented
Indicates that a question has been posed or displayed to an entity for consideration or response.
- 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_69f349a3363081909cea4c9a848cefe2 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f70b966860819089cf92927f47c5f1 |
completed | May 3, 2026, 8:47 a.m. |
| PD | Predicate disambiguation | batch_69f70ac0170c819098e3b8e41d02efef |
completed | May 3, 2026, 8:43 a.m. |
Created at: May 1, 2026, 1:51 a.m.