Triple

T19102020
Position Surface form Disambiguated ID Type / Status
Subject Shipki village E467555 entity
Predicate hasLanguage P15 FINISHED
Object Tibetan 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: Tibetan | Statement: [Shipki village, hasLanguage, Tibetan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tibetan
Context triple: [Shipki village, hasLanguage, 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. Bhutia
    Bhutia is a Sino-Tibetan language spoken primarily by the Bhutia community in the Himalayan regions of India, especially in Sikkim and parts of West Bengal.
  • C. Dholuo
    Dholuo is a Nilotic language spoken primarily by the Luo people of western Kenya and parts of Tanzania.
  • D. Dzongkha
    Dzongkha is a Sino-Tibetan language spoken primarily in Bhutan, where it serves as the national and administrative language.
  • E. Tangut
    Tangut is an extinct Tibeto-Burman language once used in the Western Xia dynasty, best known today for its large and complex logographic writing system.
  • 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_69d8dd05ac4c8190b1967d8f97f3fb2f completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e36e9bfc8190bbaccab169394d99 completed April 20, 2026, 8:27 a.m.
Created at: April 10, 2026, 12:04 p.m.