Triple

T8903501
Position Surface form Disambiguated ID Type / Status
Subject Tujia E211988 entity
Predicate language P15 FINISHED
Object Tujia language E184498 NE 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: Tujia language | Statement: [Tujia, language, Tujia language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tujia language
Context triple: [Tujia, language, Tujia language]
  • A. Tujia language chosen
    The Tujia language is a Sino-Tibetan language spoken primarily by the Tujia ethnic group in parts of central China, notably in mountainous areas of Hubei, Hunan, and neighboring provinces.
  • B. Chaoshan language
    The Chaoshan language is a Southern Min Chinese variety spoken primarily in the Chaoshan region of eastern Guangdong, known for its distinct phonology and strong cultural identity among Teochew and Swatow communities.
  • C. Kangjia language
    The Kangjia language is a lesser-known Mongolic language spoken by the Kangjia people in parts of northwestern China.
  • D. Tigak language
    The Tigak language is an Austronesian language spoken by the Tigak people of New Ireland Province in Papua New Guinea.
  • E. Tyap language
    Tyap language is a Plateau language of the Niger-Congo family spoken predominantly by the Atyap people in southern Kaduna State, Nigeria.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69ca839255248190b43984294abd92ae completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc64c091d08190b59e54eb4a184e41 completed April 1, 2026, 12:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfba26bc7881908639e9a812dec894 completed April 3, 2026, 1:01 p.m.
Created at: March 30, 2026, 6:55 p.m.