Triple

T37104709
Position Surface form Disambiguated ID Type / Status
Subject Pingtang County E918809 entity
Predicate hasSpokenLanguages P35567 FINISHED
Object Southwestern Mandarin NE NERFINISHED

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: Southwestern Mandarin | Statement: [Pingtang County, hasSpokenLanguages, Southwestern Mandarin]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasSpokenLanguages
Context triple: [Pingtang County, hasSpokenLanguages, Southwestern Mandarin]
  • A. languagesSpoken
    Indicates that an entity is able to communicate using one or more specified languages.
  • B. includesLanguagesSpokenBy
    Indicates that one entity contains or covers the set of languages spoken by another entity.
  • C. hasLanguages chosen
    Indicates that an entity is associated with one or more languages it uses, supports, or is expressed in.
  • D. includesLanguagesSpokenAlong
    Indicates that something (such as a region, route, or area) encompasses or contains the set of languages spoken along its extent or within its boundaries.
  • E. isSpokenLanguage
    Indicates that a language is used primarily for oral communication by speakers, as opposed to being only written or symbolic.
  • 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_69f76e9b99c8819096164b21ff5bd996 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fedfd913f48190bdcd450980868d9a completed May 9, 2026, 7:18 a.m.
PD Predicate disambiguation batch_69fedf58c6e88190821a7156054c9086 completed May 9, 2026, 7:16 a.m.
Created at: May 3, 2026, 4:14 p.m.