Triple

T16900035
Position Surface form Disambiguated ID Type / Status
Subject Tu E424410 entity
Predicate primaryLanguage P238 FINISHED
Object Tu language E989830 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: Tu language | Statement: [Tu, primaryLanguage, Tu language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tu language
Context triple: [Tu, primaryLanguage, Tu language]
  • A. Tu language chosen
    Tu language is a Mongolic language spoken primarily by the Tu (Monguor) people in northwestern China, especially in Qinghai and Gansu provinces.
  • B. Tem language
    Tem is a Gur language of the Niger-Congo family spoken primarily in Togo and neighboring West African countries.
  • C. Mon language
    Mon language is an Austroasiatic language historically spoken in parts of Myanmar and Thailand, notable for its ancient literary tradition and influence on regional scripts and cultures.
  • D. Temein languages
    The Temein languages are a small group of Eastern Sudanic languages spoken primarily in the Nuba Mountains of Sudan.
  • E. Tai Yo language
    The Tai Yo language is a Southwestern Tai language spoken by the Tai Yo ethnic group in parts of Vietnam, Laos, and Thailand.
  • 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_69d889da3e8c8190a2b118f383f0beac completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e3c8dbc6e48190be90066b82fc61db completed April 18, 2026, 6:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c7b0783c81909c87de503d5e7e3c completed May 10, 2026, 6 p.m.
Created at: April 10, 2026, 5:29 a.m.