Triple

T17596245
Position Surface form Disambiguated ID Type / Status
Subject Organon E428579 entity
Predicate hasPart P35 FINISHED
Object Prior Analytics NE NERFINISHED

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: Prior Analytics | Statement: [Organon, hasPart, Prior Analytics]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Prior Analytics
Context triple: [Organon, hasPart, Prior Analytics]
  • A. Prior Analytics chosen
    Prior Analytics is Aristotle’s foundational treatise on formal logic, in which he systematically develops the theory of syllogistic reasoning.
  • B. Prior Analytics, Book I
    Prior Analytics, Book I is the first book of Aristotle’s foundational treatise on formal logic, in which he systematically develops the theory of syllogistic reasoning.
  • C. Later Analytics
    Later Analytics is a foundational Aristotelian treatise on scientific knowledge and demonstration, traditionally known by its Latin title "Posterior Analytics."
  • D. Analytica Priora
    Analytica Priora is Aristotle’s foundational treatise on syllogistic logic, in which he systematically analyzes deductive reasoning and formal argument structures.
  • E. Prior
    Prior is a surname most notably associated with Arthur Prior, a pioneering logician and founder of modern tense logic.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889e1030481909950e140c63255b9 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e469ec335c8190abcaff700cfff23b completed April 19, 2026, 5:36 a.m.
Created at: April 10, 2026, 5:51 a.m.