Triple
T29562857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turán's theorem |
E750082
|
entity |
| Predicate | edgeCountType |
P114495
|
FINISHED |
| Object | exact formula |
—
|
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: exact formula | Statement: [Turán's theorem, edgeCountType, exact formula]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: edgeCountType Context triple: [Turán's theorem, edgeCountType, exact formula]
-
A.
edgeMultiplicity
Indicates how many parallel or repeated connections (edges) exist between the same pair of entities in a relationship.
-
B.
hasEdgeCount
chosen
Indicates that there is a specified number of edges associated with an entity, such as a graph or geometric shape.
-
C.
edgeType
Indicates the specific kind or category of connection that exists between two related entities.
-
D.
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).
-
E.
hasEdgeCountRelation
Indicates a relationship where one entity’s number of edges is compared to or associated with another value or entity’s edge count.
- 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_69f6659d36208190b01412600a4ed57d |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 5:21 p.m.