Triple

T15918641
Position Surface form Disambiguated ID Type / Status
Subject Szekeres–Lindström theorem E386034 entity
Predicate hasProofTechnique P7024 FINISHED
Object combinatorial arguments 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: combinatorial arguments | Statement: [Szekeres–Lindström theorem, hasProofTechnique, combinatorial arguments]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasProofTechnique
Context triple: [Szekeres–Lindström theorem, hasProofTechnique, combinatorial arguments]
  • A. hasProofMethod chosen
    Indicates that there exists a specific method or technique used to establish or demonstrate the validity of something (such as a statement, claim, or theorem).
  • B. hasTechnique
    Indicates that an entity employs, utilizes, or is associated with a particular method, procedure, or technique.
  • C. hasAlternativeProofMethod
    Indicates that there exists a different proof technique or approach that can be used to establish the same result or theorem.
  • D. hasProofCount
    Indicates the number of proofs or supporting evidential items associated with a given entity or claim.
  • E. usesProofLanguage
    Indicates that one entity employs a specific formal or structured language to express or present a proof related to another entity.
  • 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_69d86da686e4819097cbf3b1fc2d881d completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e172b48b308190bc430b2308cbc75b completed April 16, 2026, 11:37 p.m.
PD Predicate disambiguation batch_69e142cf5c548190a931f7b58144cd31 completed April 16, 2026, 8:13 p.m.
Created at: April 10, 2026, 4:52 a.m.