Triple
T29562856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turán's theorem |
E750082
|
entity |
| Predicate | edgeCountFormula |
P114495
|
FINISHED |
| Object | floor(((r-2)/(2(r-1))) * n^2) |
—
|
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: floor(((r-2)/(2(r-1))) * n^2) | Statement: [Turán's theorem, edgeCountFormula, floor(((r-2)/(2(r-1))) * n^2)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: edgeCountFormula Context triple: [Turán's theorem, edgeCountFormula, floor(((r-2)/(2(r-1))) * n^2)]
-
A.
hasEdgeCount
chosen
Indicates that there is a specified number of edges associated with an entity, such as a graph or geometric shape.
-
B.
edgeMultiplicity
Indicates how many parallel or repeated connections (edges) exist between the same pair of entities in a relationship.
-
C.
hasEdgeCountRelation
Indicates a relationship where entities are compared or linked based on the number of edges they have (e.g., in a graph or network structure).
-
D.
hasEdgeCountRelation
Indicates a relationship where one entity’s number of edges is compared to or associated with another value or entity’s edge count.
-
E.
edgeCountDistributionInG(n,p)
Indicates how the number of edges is probabilistically distributed in a random graph with n nodes where each possible edge is included independently with probability p.
- 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_69f0bd4919e48190942b2a13d5b97d03 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f66d1e64e8819080579603e5bcdeb7 |
completed | May 2, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f6633ac8a88190ab0cda62bbfcf9b0 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 28, 2026, 5:21 p.m.