Triple
T23624730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lipton–Tarjan separator theorem |
E583430
|
entity |
| Predicate | separatorSizeBound |
P142698
|
FINISHED |
| Object | O(sqrt(n)) |
—
|
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: O(sqrt(n)) | Statement: [Lipton–Tarjan separator theorem, separatorSizeBound, O(sqrt(n))]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: separatorSizeBound Context triple: [Lipton–Tarjan separator theorem, separatorSizeBound, O(sqrt(n))]
-
A.
divisionSize
Indicates the size or magnitude of a division or subdivided part in relation to a whole.
-
B.
borderSectionLength
Indicates the measured length of a specific segment of a shared border between two geographic or administrative areas.
-
C.
rangeSize
Indicates the extent or magnitude of the range over which something applies, varies, or is distributed.
-
D.
dimensionBoundType
Indicates the type or nature of the constraint that bounds a given dimension in a relationship.
-
E.
sizeRestriction
chosen
Indicates that there is a limitation or constraint on the allowable size or dimensions of something in the relationship.
- 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.