Triple
T12966080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Critical Analysis and Reasoning Skills |
E321265
|
entity |
| Predicate | questionsPerPassage |
P107734
|
FINISHED |
| Object | 5 to 7 |
—
|
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: 5 to 7 | Statement: [Critical Analysis and Reasoning Skills, questionsPerPassage, 5 to 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: questionsPerPassage Context triple: [Critical Analysis and Reasoning Skills, questionsPerPassage, 5 to 7]
-
A.
numberOfPassages
Indicates the total count of distinct passages associated with or contained within a given entity or context.
-
B.
numberOfQuestions
Indicates the total count of questions associated with or contained in a given entity or context.
-
C.
numberOfEssays
Indicates the quantity of essays associated with a given entity or context.
-
D.
questionType
Indicates the specific category or kind of question that an item, query, or prompt belongs to.
-
E.
soughtPassage
Indicates that one entity attempted to obtain or gain access to a particular passage, route, or way through something.
- 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_69d80763bd6c819094437da5b20b01d2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97dba57988190b786ffed55687a72 |
completed | April 10, 2026, 10:46 p.m. |
| PDg | Predicate description generation | batch_69d97e5811f481908178fac6d2e0efcd |
completed | April 10, 2026, 10:48 p.m. |
Created at: April 9, 2026, 8:28 p.m.