Triple

T35237150
Position Surface form Disambiguated ID Type / Status
Subject Normalized Cuts for image segmentation E1017405 entity
Predicate segmentationObtainedBy P90051 FINISHED
Object thresholding eigenvector components 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: thresholding eigenvector components | Statement: [Normalized Cuts for image segmentation, segmentationObtainedBy, thresholding eigenvector components]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: segmentationObtainedBy
Context triple: [Normalized Cuts for image segmentation, segmentationObtainedBy, thresholding eigenvector components]
  • A. segmentation
    Indicates dividing something into distinct parts or segments based on certain criteria or boundaries.
  • B. imageSeparationMethod chosen
    Indicates the technique or process used to separate or distinguish different components, regions, or elements within an image.
  • C. segregatedIn
    Indicates that one entity is separated or isolated within a specific space, group, or context defined by another entity.
  • D. segmentAppearance
    Indicates how a particular segment is visually or perceptually presented or manifested.
  • E. segmentBy
    Indicates dividing something into distinct parts or sections based on a specified criterion or boundary.
  • 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.