Triple

T16005589
Position Surface form Disambiguated ID Type / Status
Subject Pronounced ‘Lĕh-’nérd ‘Skin-’nérd E388207 entity
Predicate hasTitlePronunciationNote P103348 FINISHED
Object title spells out pronunciation of 'Lynyrd Skynyrd' 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: title spells out pronunciation of 'Lynyrd Skynyrd' | Statement: [Pronounced ‘Lĕh-’nérd ‘Skin-’nérd, hasTitlePronunciationNote, title spells out pronunciation of 'Lynyrd Skynyrd']
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasTitlePronunciationNote
Context triple: [Pronounced ‘Lĕh-’nérd ‘Skin-’nérd, hasTitlePronunciationNote, title spells out pronunciation of 'Lynyrd Skynyrd']
  • A. hasTitleInRevisedRomanization
    Indicates that an entity has a specific title expressed using the Revised Romanization system for Korean.
  • B. hasPronunciationInformation chosen
    Indicates that there is available information describing how something is pronounced.
  • C. hasPronunciationDifferenceFrom
    Indicates that two linguistic items differ in how they are pronounced.
  • D. hasTitleInEnglishOrthography
    Indicates that an entity has a specific title expressed using English spelling and writing conventions.
  • E. hasTitleAccentMarks
    Indicates that the title contains one or more accented characters or diacritical marks.
  • 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_69d86dabcb7c8190b6a39d6831d2fa1b completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e173b3bf6c81909230170e833d7ce7 completed April 16, 2026, 11:41 p.m.
PD Predicate disambiguation batch_69e142dc081c819082527e3fa8773460 completed April 16, 2026, 8:13 p.m.
Created at: April 10, 2026, 4:55 a.m.