Triple

T10269843
Position Surface form Disambiguated ID Type / Status
Subject Chern–Simons theory E240804 entity
Predicate levelQuantizationCondition P68585 FINISHED
Object k ∈ ℤ for compact simple gauge groups 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: k ∈ ℤ for compact simple gauge groups | Statement: [Chern–Simons theory, levelQuantizationCondition, k ∈ ℤ for compact simple gauge groups]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: levelQuantizationCondition
Context triple: [Chern–Simons theory, levelQuantizationCondition, k ∈ ℤ for compact simple gauge groups]
  • A. hasQuantizationCondition chosen
    Indicates that a system, parameter, or quantity is constrained to take on only discrete (often integer-related) values according to a specific quantization rule or condition.
  • B. quantizationIs
    Indicates that one entity is a specific quantization or discretized representation of another entity.
  • C. levelNotation
    Indicates the specific symbolic or textual notation used to represent the level, degree, or rank of something within a defined scale or hierarchy.
  • D. isQuantizedBy
    Indicates that a continuous or variable quantity is represented or constrained using discrete units, levels, or steps defined by another entity.
  • E. controlGranularity
    Indicates the level of detail or fineness with which control or regulation is applied within a given process or system.
  • 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_69d381a94c1881908fc38fc263d9b9c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d2872830819080fdfa816167d04c completed April 7, 2026, 9:46 a.m.
PD Predicate disambiguation batch_69d4d1ef6e6c81908a8ee52e4d28127b completed April 7, 2026, 9:44 a.m.
Created at: April 6, 2026, 11:35 a.m.