Triple
T13507048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Complexity of Theorem-Proving Procedures |
E321037
|
entity |
| Predicate | problemTypeStudied |
P83422
|
FINISHED |
| Object | decision problems in propositional logic |
—
|
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: decision problems in propositional logic | Statement: [The Complexity of Theorem-Proving Procedures, problemTypeStudied, decision problems in propositional logic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: problemTypeStudied Context triple: [The Complexity of Theorem-Proving Procedures, problemTypeStudied, decision problems in propositional logic]
-
A.
problemType
chosen
Indicates the specific category or classification of a problem within a defined problem space or system.
-
B.
problemStatement
Indicates that an entity presents, defines, or expresses a specific problem or issue to be addressed.
-
C.
studyType
Indicates the kind or category of study or research methodology associated with an entity or activity.
-
D.
numberOfProblems
Indicates the quantity or count of problems associated with a given entity or situation.
-
E.
correctedProblem
Indicates that one entity has fixed or amended an error or issue present in another entity.
- 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_69d807629d6c8190998f1b9bb12d2ed0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaf8259a08190ada13c4a3078f07d |
completed | April 12, 2026, 2:43 p.m. |
| PD | Predicate disambiguation | batch_69dbae0b63748190b5e207f84b2532ea |
completed | April 12, 2026, 2:36 p.m. |
Created at: April 9, 2026, 9:43 p.m.