Triple
T23624742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lipton–Tarjan separator theorem |
E583430
|
entity |
| Predicate | complexityImpact |
P20527
|
FINISHED |
| Object | enables faster algorithms for many NP-hard problems on planar graphs |
—
|
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: enables faster algorithms for many NP-hard problems on planar graphs | Statement: [Lipton–Tarjan separator theorem, complexityImpact, enables faster algorithms for many NP-hard problems on planar graphs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: complexityImpact Context triple: [Lipton–Tarjan separator theorem, complexityImpact, enables faster algorithms for many NP-hard problems on planar graphs]
-
A.
controlsComplexityBy
Indicates that one entity manages, limits, or regulates the complexity of another entity, process, or system.
-
B.
hasComplexity
Indicates that something possesses a certain level or type of complexity, often in terms of structure, behavior, or difficulty.
-
C.
complexityStatus
Indicates the current level or state of complexity associated with an entity or process.
-
D.
impactOnPerformance
chosen
Indicates that one entity has an effect, influence, or consequence on the performance level or effectiveness of another entity.
-
E.
encodingImpact
Indicates how one encoding or encoding choice affects, modifies, or constrains another process, representation, or outcome.
- 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_69e248fc8d74819091bd5baef2f36f6f |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b17be6288190a409df700c1003bd |
completed | April 29, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69f118d0e0588190a86527a7747c5427 |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:46 p.m.