Triple

T672129
Position Surface form Disambiguated ID Type / Status
Subject All for one and one for all E12993 entity
Predicate hasNotableTranslation P2303 FINISHED
Object Uno para todos y todos para uno 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: Uno para todos y todos para uno | Statement: [All for one and one for all, hasNotableTranslation, Uno para todos y todos para uno]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasNotableTranslation
Context triple: [All for one and one for all, hasNotableTranslation, Uno para todos y todos para uno]
  • A. hasTranslation chosen
    Indicates that one entity is a translation or translated version of another entity in a different language.
  • B. hasNotableWord
    Indicates that an entity is associated with a word or term that is considered notable, distinctive, or significant in some context.
  • C. hasNotableSubject
    Indicates that an entity is associated with a subject that is particularly significant, prominent, or noteworthy in relation to it.
  • D. hasNotableFeature
    Indicates that an entity possesses a specific characteristic, trait, or attribute that is considered significant or noteworthy.
  • E. hasSignificantLanguage
    Indicates that an entity possesses a language that plays an important or primary role in its communication, identity, or functioning.
  • 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_69a493355dec819098d4244b2fa34885 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4a1b3682c8190a9b9a454480c3446 completed March 1, 2026, 8:29 p.m.
PD Predicate disambiguation batch_69a49d1a16c48190af89e3b078a4957e completed March 1, 2026, 8:10 p.m.
Created at: March 1, 2026, 7:36 p.m.