Triple

T31305951
Position Surface form Disambiguated ID Type / Status
Subject Hunan linguistic area E798336 entity
Predicate hasTypeOfIsogloss P197202 FINISHED
Object phonological isoglosses 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: phonological isoglosses | Statement: [Hunan linguistic area, hasTypeOfIsogloss, phonological isoglosses]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasTypeOfIsogloss
Context triple: [Hunan linguistic area, hasTypeOfIsogloss, phonological isoglosses]
  • A. sharesIsoglossWith
    Indicates that two linguistic varieties share a common isogloss, i.e., they exhibit the same geographically bounded linguistic feature or boundary.
  • B. hasISO639Type
    Indicates the classification of a language resource according to its ISO 639 code type (e.g., ISO 639-1, 639-2, 639-3).
  • C. hasGlottologEntryType
    Indicates that a glottolog entry is classified as having a specific type or category within the Glottolog database.
  • D. hasLinguisticVariationType
    Indicates that one linguistic form is related to another by a specific type of variation, such as dialectal, orthographic, morphological, or phonological difference.
  • E. hasLanguageType
    Indicates that an entity is associated with a particular type or category of language (e.g., spoken, written, programming, sign).
  • 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_69f224e0bd4c8190aab9b29a73f7aa3c completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69fe7bfc94bc81909eeec946e8c1c450 completed May 9, 2026, 12:12 a.m.
PD Predicate disambiguation batch_69fe7b74a1188190886f128e07f712da completed May 9, 2026, 12:10 a.m.
PDg Predicate description generation batch_69fe7bfb71b08190bed5c33e4ab7afff completed May 9, 2026, 12:12 a.m.
Created at: April 29, 2026, 9:14 p.m.