Triple
T35237137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Normalized Cuts for image segmentation |
E1017405
|
entity |
| Predicate | similarityCanBeBasedOn |
P94048
|
FINISHED |
| Object | intensity |
—
|
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: intensity | Statement: [Normalized Cuts for image segmentation, similarityCanBeBasedOn, intensity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: similarityCanBeBasedOn Context triple: [Normalized Cuts for image segmentation, similarityCanBeBasedOn, intensity]
-
A.
hasSimilarityTo
Indicates that one entity shares common characteristics, features, or qualities with another entity to a notable degree.
-
B.
similarityReason
chosen
Indicates that there is an identified basis or explanation for why two entities are considered similar.
-
C.
namedForSimilarityTo
Indicates that one entity is given its name because of a perceived resemblance or likeness to another entity.
-
D.
lessSimilarTo
Indicates that one entity is considered to share fewer similarities or a weaker resemblance with another entity compared to some reference or alternative.
-
E.
logicalCompatibilityWith
Indicates that two entities can coexist, interact, or be combined without contradiction under a given set of logical rules or assumptions.
- 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.