Triple

T4552391
Position Surface form Disambiguated ID Type / Status
Subject Hardy–Littlewood circle method E120394 entity
Predicate formalSetting P57964 FINISHED
Object analysis on the torus 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: analysis on the torus | Statement: [Hardy–Littlewood circle method, formalSetting, analysis on the torus]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: formalSetting
Context triple: [Hardy–Littlewood circle method, formalSetting, analysis on the torus]
  • A. formalFunction
    Indicates that an entity serves an official or designated role or purpose within a formal structure, system, or context.
  • B. formalityLevel
    Indicates the degree of social or stylistic formality characterizing an interaction, expression, or context between entities.
  • C. formalDegreeTrack
    Indicates that an entity is enrolled in or associated with an official, structured academic degree program or course of study.
  • D. formalization
    Indicates that an informal concept, process, or agreement is being expressed, structured, or codified in a formal, explicit, and often standardized way.
  • E. ceremonialVenueFunction
    Indicates that a venue serves a role or purpose specifically related to hosting or supporting ceremonial events or activities.
  • F. None of above. chosen

Provenance (4 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_69bd4636f1648190a701445c2fcd9c17 completed March 20, 2026, 1:05 p.m.
NER Named-entity recognition batch_69bd57f7b9748190af29d02fc77b02e0 completed March 20, 2026, 2:21 p.m.
PD Predicate disambiguation batch_69bd5223423c81908317351b58cff5f5 completed March 20, 2026, 1:56 p.m.
PDg Predicate description generation batch_69bd56b4a9508190acdb888eef18f1ee completed March 20, 2026, 2:16 p.m.
Created at: March 20, 2026, 1:09 p.m.