Triple

T23142544
Position Surface form Disambiguated ID Type / Status
Subject graph Laplacian E577498 entity
Predicate centralConceptIn P533 FINISHED
Object spectral graph theory NE NERFINISHED

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: spectral graph theory | Statement: [graph Laplacian, centralConceptIn, spectral graph theory]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: spectral graph theory
Context triple: [graph Laplacian, centralConceptIn, spectral graph theory]
  • A. Spectral Graph Theory chosen
    Spectral Graph Theory is a mathematical field that studies graphs through the eigenvalues and eigenvectors of matrices associated with them, such as adjacency and Laplacian matrices, with applications across combinatorics, computer science, and network analysis.
  • B. Laplacian spectrum
    The Laplacian spectrum is the collection of eigenvalues of the Laplace operator on a domain or manifold, encoding how functions vibrate or diffuse over it and serving as a key tool in spectral geometry and mathematical physics.
  • C. graph theory
    Graph theory is a branch of mathematics that studies the properties and applications of graphs, which model pairwise relationships between objects using vertices and edges.
  • D. Convex Optimization of Graph Laplacian Eigenvalues
    "Convex Optimization of Graph Laplacian Eigenvalues" is a research work by Stephen P. Boyd that develops convex optimization methods to analyze and design graphs via the spectral properties of their Laplacian matrices.
  • E. spectral geometry
    Spectral geometry is a field of mathematics that studies how the geometric and topological properties of spaces are reflected in the spectra of associated differential operators.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245f8e6248190ba3d58e068b4dccb completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18ecb72fc8190a24e8f5756217a36 completed April 29, 2026, 4:53 a.m.
Created at: April 17, 2026, 4 p.m.