Triple

T13442912
Position Surface form Disambiguated ID Type / Status
Subject Mercédès Jellinek E320408 entity
Predicate diacriticDetail P18659 FINISHED
Object contains an acute accent on the letter e 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: contains an acute accent on the letter e | Statement: [Mercédès Jellinek, diacriticDetail, contains an acute accent on the letter e]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: diacriticDetail
Context triple: [Mercédès Jellinek, diacriticDetail, contains an acute accent on the letter e]
  • A. diacriticType chosen
    Indicates the specific kind or category of diacritic mark associated with a character or symbol.
  • B. usesDiacritics
    Indicates that the referenced text or linguistic element employs diacritical marks as part of its written form.
  • C. usesDiacriticsFrom
    Indicates that one entity employs or incorporates the diacritical marks that originate from or are characteristic of another entity.
  • D. usesToneMarks
    Indicates that one entity applies or includes diacritical tone marks in the representation or transcription of another entity (such as text, language, or symbols).
  • E. hasAccent
    Indicates that an entity speaks with or possesses a particular accent or distinctive pronunciation style.
  • 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_69d80761e6cc8190a90c844589998ecc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaee881888190811ddf01bc699864 completed April 12, 2026, 2:40 p.m.
PD Predicate disambiguation batch_69d9a03ce03481908c61094f0cc0c158 completed April 11, 2026, 1:13 a.m.
Created at: April 9, 2026, 9:40 p.m.