Triple
T21088307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karp reduction |
E519560
|
entity |
| Predicate | complexityClassContext |
P62369
|
FINISHED |
| Object | NP |
—
|
NE NERFINISHED |
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: NP | Statement: [Karp reduction, complexityClassContext, NP]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NP Context triple: [Karp reduction, complexityClassContext, NP]
-
A.
NP
NP was the reporting mark used by the historic Northern Pacific Railway, a major transcontinental railroad in the northern United States.
-
B.
NP
NP is a UK postcode area covering parts of Newport and surrounding regions in south-east Wales.
-
C.
NP
NP is the abbreviation commonly used for the National Party, the former ruling political party of apartheid-era South Africa.
-
D.
NP
chosen
NP (nondeterministic polynomial time) is the complexity class of decision problems for which proposed solutions can be verified in polynomial time by a deterministic Turing machine.
-
E.
PN
PN is the vehicle registration code used for the Italian city and province of Pordenone in the Friuli Venezia Giulia region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b507dd9081908fb8bfcbef4c8b46 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7094cebe08190bb10f51a45c244ec |
completed | April 21, 2026, 5:21 a.m. |
Created at: April 16, 2026, 2:50 p.m.