Triple

T17592403
Position Surface form Disambiguated ID Type / Status
Subject Han E428478 entity
Predicate hasLinguisticGroup P3349 FINISHED
Object Gan Chinese 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: Gan Chinese | Statement: [Han, hasLinguisticGroup, Gan Chinese]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gan Chinese
Context triple: [Han, hasLinguisticGroup, Gan Chinese]
  • A. Gan Chinese chosen
    Gan Chinese is a major Sinitic language variety spoken primarily in Jiangxi province and surrounding regions in southeastern China.
  • B. Hán
    Hán is the pinyin transcription of the name of the ancient Chinese State of Han, one of the major states during the Warring States period.
  • C. Xiang Chinese
    Xiang Chinese is a major Sinitic language variety spoken primarily in Hunan province and surrounding regions in south-central China.
  • D. Jin Chinese
    Jin Chinese is a major Sinitic language variety spoken primarily in Shanxi and surrounding regions of northern China, often considered distinct from standard Mandarin due to its unique phonological and lexical features.
  • E. Wu Chinese
    Wu Chinese is a major Sinitic language group spoken primarily in Shanghai, southern Jiangsu, and Zhejiang, known for its rich tonal system and significant phonological differences from Mandarin.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889e1030481909950e140c63255b9 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e469e79dac8190953a1ce8fc015b20 completed April 19, 2026, 5:36 a.m.
Created at: April 10, 2026, 5:51 a.m.