Triple
T2779369
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quantitative Reasoning |
E61654
|
entity |
| Predicate | questionFormat |
P12351
|
FINISHED |
| Object | multiple choice |
—
|
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: multiple choice | Statement: [Quantitative Reasoning, questionFormat, multiple choice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: questionFormat Context triple: [Quantitative Reasoning, questionFormat, multiple choice]
-
A.
questionForm
Indicates that one entity is expressed or structured in the form of a question directed toward another entity or context.
-
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.
format
Indicates the specific arrangement, structure, or presentation style in which something is organized or expressed.
-
E.
relatedFormat
Indicates that two resources are available in different but closely related formats or media representations of essentially the same content.
- 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_69ab4b7e43c48190997b8fc8fb1663ab |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abddceb9d88190961e30d521a21552 |
completed | March 7, 2026, 8:11 a.m. |
| PD | Predicate disambiguation | batch_69abdd00b65c8190a8ea444308c4fa2b |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:57 p.m.