Triple

T12275926
Position Surface form Disambiguated ID Type / Status
Subject Boston English E292587 entity
Predicate hasOrthographicRepresentation P12752 FINISHED
Object eye-dialect spellings like "pahk" for "park" 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: eye-dialect spellings like "pahk" for "park" | Statement: [Boston English, hasOrthographicRepresentation, eye-dialect spellings like "pahk" for "park"]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasOrthographicRepresentation
Context triple: [Boston English, hasOrthographicRepresentation, eye-dialect spellings like "pahk" for "park"]
  • A. hasOrthographicPreference
    Indicates that one entity prefers or selects a particular written or spelling form of another entity.
  • B. orthographicProperty chosen
    Indicates a relationship where a specific written or spelling-related characteristic is attributed to or associated with an entity.
  • C. hasOrthographicConvention
    Indicates that there is a specific writing or spelling convention that governs how something is represented in written form.
  • D. hasOrthographicReform
    Indicates that an entity has undergone or is associated with a change or standardization in its writing system or spelling conventions.
  • E. orthographicVariant
    Indicates that two written forms are different spellings or orthographic representations of the same linguistic item.
  • 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_69d6ab6856488190b5d31178d5015f8e completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d9380a5e78819086bd4dfe9a83d1f5 completed April 10, 2026, 5:48 p.m.
PD Predicate disambiguation batch_69d91c4a66cc819083ce6fcaf5042af6 completed April 10, 2026, 3:50 p.m.
Created at: April 8, 2026, 9:52 p.m.