Triple

T24649177
Position Surface form Disambiguated ID Type / Status
Subject Alphabetic Presentation Forms E610198 entity
Predicate containsCompatibilityCharactersFor P64709 FINISHED
Object Latin script 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: Latin script | Statement: [Alphabetic Presentation Forms, containsCompatibilityCharactersFor, Latin script]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: containsCompatibilityCharactersFor
Context triple: [Alphabetic Presentation Forms, containsCompatibilityCharactersFor, Latin script]
  • A. hasLanguageCharacter
    Indicates that an entity uses, contains, or is associated with a specific written or symbolic character from a language.
  • B. hasNoConventionalCharacters
    Indicates that the entity contains no standard alphanumeric or commonly used written characters.
  • C. hasDistinctCharacterSet
    Indicates that two compared items use different sets of characters, with no character set being a subset or duplicate of the other.
  • D. characterCoverage chosen
    Indicates that one entity provides or includes sufficient representation or support for the characters (e.g., glyphs, symbols, or scripts) required or used by another entity.
  • E. hasUnicode
    Indicates that an entity is associated with, represented by, or encoded using a specific Unicode character or sequence.
  • 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_69e2c4d350a481909170482bc2ce6af9 completed April 17, 2026, 11:40 p.m.
NER Named-entity recognition batch_69f5f6baf2d48190a6a4cd6501be87d2 completed May 2, 2026, 1:06 p.m.
PD Predicate disambiguation batch_69f5afd5baac8190bb8ed576813c8591 completed May 2, 2026, 8:03 a.m.
Created at: April 18, 2026, 2:33 a.m.