Triple
T26992606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Subset sum problem |
E679894
|
entity |
| Predicate | isWeaklyNPComplete |
P161756
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Subset sum problem, isWeaklyNPComplete, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isWeaklyNPComplete Context triple: [Subset sum problem, isWeaklyNPComplete, true]
-
A.
isNPComplete
Indicates that a decision problem is both in NP and NP-hard, meaning it can be verified in polynomial time and is at least as hard as any problem in NP.
-
B.
isNPHard
Indicates that solving the associated problem is at least as hard as the hardest problems in NP, so no known polynomial-time algorithm can solve all its instances unless P = NP.
-
C.
yearNPCompletenessProved
Indicates the year in which the NP-completeness of a given problem was formally proved.
-
D.
firstNPCompleteProblem
Indicates that the subject is the earliest or original problem proven to be NP-complete within a given context or theory.
-
E.
relationToNPCompleteness
Indicates that the subject has a defined conceptual or formal connection to the notion of NP-completeness (e.g., being NP-complete, related to NP-complete problems, or used in reasoning about NP-completeness).
- 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_69eeeb5138ac8190b3c273ddc659a54f |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f621915ee48190b508025afa2fb4fc |
completed | May 2, 2026, 4:08 p.m. |
| PD | Predicate disambiguation | batch_69f61b3ee7b08190a0a1bc5d26b757aa |
completed | May 2, 2026, 3:41 p.m. |
| PDg | Predicate description generation | batch_69f61f109ef48190873bfe18638d2046 |
completed | May 2, 2026, 3:58 p.m. |
Created at: April 27, 2026, 6:52 a.m.