Triple
T35237147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Normalized Cuts for image segmentation |
E1017405
|
entity |
| Predicate | graphMatrix |
P96954
|
FINISHED |
| Object | affinity matrix |
—
|
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: affinity matrix | Statement: [Normalized Cuts for image segmentation, graphMatrix, affinity matrix]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: graphMatrix Context triple: [Normalized Cuts for image segmentation, graphMatrix, affinity matrix]
-
A.
graphAnalogue
Indicates that one entity serves as a graph-theoretic counterpart or structural analogue of another entity.
-
B.
hasEdgeGraph
Indicates that there is an edge (a direct connection or link) present within a graph between specified nodes or components.
-
C.
dependencyGraph
Indicates a relationship where one entity’s existence, behavior, or outcome depends on one or more other entities, forming a structured network of such dependencies.
-
D.
associatedCayleyGraph
Indicates that there is a Cayley graph constructed from, or corresponding to, the given algebraic structure or group.
-
E.
usesGraphType
chosen
Indicates that one entity employs or is configured to operate with a specific type of graph representation or graph model.
- 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_69f76de235048190b990070c23c51b6b |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78f63c8788190b253a18de5ca1312 |
completed | May 3, 2026, 6:09 p.m. |
| PD | Predicate disambiguation | batch_69f78e2d71248190b850c2802ec170c0 |
completed | May 3, 2026, 6:04 p.m. |
Created at: May 3, 2026, 4:02 p.m.