Triple

T5041268
Position Surface form Disambiguated ID Type / Status
Subject Fundamento de Esperanto E113548 entity
Predicate hasMultilingualGlosses P60969 FINISHED
Object French 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: French | Statement: [Fundamento de Esperanto, hasMultilingualGlosses, French]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasMultilingualGlosses
Context triple: [Fundamento de Esperanto, hasMultilingualGlosses, French]
  • A. hasNeighboringLanguages
    Indicates that two languages are geographically or regionally adjacent to each other in their areas of use.
  • B. hasTranslation
    Indicates that one entity is a translation or translated version of another entity in a different language.
  • C. hasAcronymExpansionLanguage
    Indicates that a specified language is the language in which an acronym’s full expansion is expressed.
  • D. hasLanguageRepresentation
    Indicates that an entity is expressed, encoded, or represented using a particular natural or formal language.
  • E. hasLanguageOfSurroundingCountries
    Indicates that an entity uses or includes the languages commonly spoken in the countries that geographically surround it.
  • 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_69bd44384298819089c49e7c330ec7b8 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd73de73008190b89aec9a76b43e4f completed March 20, 2026, 4:20 p.m.
PD Predicate disambiguation batch_69bd71529d608190a53470ba6c14bb1d completed March 20, 2026, 4:09 p.m.
PDg Predicate description generation batch_69bd73617f348190b2fa68a0ef4fc7b1 completed March 20, 2026, 4:18 p.m.
Created at: March 20, 2026, 1:37 p.m.