Triple

T2373580
Position Surface form Disambiguated ID Type / Status
Subject Hopfield network E46142 entity
Predicate hasApproximateCapacity P21034 FINISHED
Object 0.138N for random uncorrelated patterns 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: 0.138N for random uncorrelated patterns | Statement: [Hopfield network, hasApproximateCapacity, 0.138N for random uncorrelated patterns]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasApproximateCapacity
Context triple: [Hopfield network, hasApproximateCapacity, 0.138N for random uncorrelated patterns]
  • A. approximateCapacity chosen
    Indicates that one entity has an estimated or rough capacity value relative to another or to a specified measure.
  • B. hasCapacityTo
    Indicates that one entity possesses the ability, power, or potential to perform an action or bring about a particular effect in relation to another entity or context.
  • C. hasApproximateMemberCount
    Indicates that an entity is associated with a group or collection for which only an estimated or non-exact number of members is known.
  • D. hasMaxLengthApprox
    Indicates that something has a maximum length that is approximately equal to a specified value, allowing for some tolerance or imprecision.
  • E. hasApproximateExtent
    Indicates that one entity has a spatial, temporal, or quantitative extent that is only roughly or approximately specified rather than exact.
  • 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_69a88a145268819083e2736cb835c696 completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abca4d89248190be7d712d5fa8382b completed March 7, 2026, 6:48 a.m.
PD Predicate disambiguation batch_69abc59d82f08190b7c36982d1ae783d completed March 7, 2026, 6:28 a.m.
Created at: March 4, 2026, 7:56 p.m.