Triple

T34415980
Position Surface form Disambiguated ID Type / Status
Subject Negation E883403 entity
Predicate contradictionFormulation P127841 FINISHED
Object not both p and not p 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: not both p and not p | Statement: [Negation, contradictionFormulation, not both p and not p]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: contradictionFormulation
Context triple: [Negation, contradictionFormulation, not both p and not p]
  • A. contradictoryPairs chosen
    Indicates that the paired entities stand in direct logical opposition such that the truth of one necessarily implies the falsity of the other.
  • B. contradictedTheory
    Indicates that one entity has presented evidence, arguments, or findings that oppose, challenge, or invalidate the theory proposed by another entity.
  • C. negativeFormulation
    Indicates that the associated statement, condition, or requirement is expressed in a negated or prohibitive form rather than an affirmative one.
  • D. paradoxType
    Indicates the specific kind or category of paradox that characterizes the relationship or situation.
  • E. hasFormulation
    Indicates that one entity is expressed, prepared, or configured in a particular form or composition defined by 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_69f349c2e3b88190a67834eb5bcffeaf completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69feafa1ba0081909013800b85a9f613 completed May 9, 2026, 3:53 a.m.
PD Predicate disambiguation batch_69feae58d62c81909d031f3df8992883 completed May 9, 2026, 3:47 a.m.
Created at: May 1, 2026, 1:59 a.m.