Triple
T495102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GRE |
E10274
|
entity |
| Predicate | quantQuestionTypes |
P12351
|
FINISHED |
| Object | problem solving |
—
|
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: problem solving | Statement: [GRE, quantQuestionTypes, problem solving]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: quantQuestionTypes Context triple: [GRE, quantQuestionTypes, problem solving]
-
A.
questionType
chosen
Indicates the specific category or kind of question that an item, query, or prompt belongs to.
-
B.
quantifies
Indicates that one entity expresses or specifies the amount, number, or degree of another entity.
-
C.
quantityType
Indicates that one entity is the type or category of quantity to which another entity (a specific measured or measurable amount) belongs.
-
D.
centralQuestion
Indicates that something is the main issue, problem, or inquiry around which a discussion, work, or investigation is focused.
-
E.
number
Indicates that one entity is associated with a specific numerical value or count in relation to another entity or context.
- 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_69a2e847df8481909239ec08ccf1e376 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f0fdd5608190815fa36485df8962 |
completed | Feb. 28, 2026, 1:43 p.m. |
| PD | Predicate disambiguation | batch_69a2edf90ca88190b6a182e5b6733612 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.