Triple

T4893428
Position Surface form Disambiguated ID Type / Status
Subject Tibetan E109616 entity
Predicate standardVariety P751 FINISHED
Object Lhasa Tibetan E109616 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: Lhasa Tibetan | Statement: [Tibetan, standardVariety, Lhasa Tibetan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lhasa Tibetan
Context triple: [Tibetan, standardVariety, Lhasa Tibetan]
  • A. Tibetan chosen
    Tibetan is a Sino-Tibetan language spoken primarily in Tibet and surrounding Himalayan regions, serving as the liturgical language of Tibetan Buddhism and a key marker of Tibetan cultural identity.
  • B. Gyel dialect
    The Gyel dialect is a regional variety of the Berom language spoken by the Berom people of central Nigeria.
  • C. Dholuo
    Dholuo is a Nilotic language spoken primarily by the Luo people of western Kenya and parts of Tanzania.
  • D. Chochenyo
    Chochenyo is an indigenous Ohlone language traditionally spoken in the East Bay region of the San Francisco Bay Area in California.
  • E. Dzongkha
    Dzongkha is a Sino-Tibetan language spoken primarily in Bhutan, where it serves as the national and administrative language.
  • 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_69bd4410bbf88190aad50d2451c863d6 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6e257b0481909fd60eb29351b6d8 completed March 20, 2026, 3:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69be6fc2f00881908cae1e68df2019e3 completed March 21, 2026, 10:15 a.m.
Created at: March 20, 2026, 1:28 p.m.