Triple

T7671694
Position Surface form Disambiguated ID Type / Status
Subject Tibeto-Burman languages E173762 entity
Predicate includesLanguage P2177 FINISHED
Object Tamang E237477 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: Tamang | Statement: [Tibeto-Burman languages, includesLanguage, Tamang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tamang
Context triple: [Tibeto-Burman languages, includesLanguage, Tamang]
  • A. Tamang chosen
    Tamang is a Sino-Tibetan language spoken primarily by the Tamang people of Nepal and the Nepali diaspora, including Nepali Americans.
  • B. Dasu
    Dasu is a town in Pakistan that serves as the administrative headquarters of Upper Kohistan District in the Hazara region of Khyber Pakhtunkhwa.
  • C. Ang Lhamu
    Ang Lhamu was the wife of famed Sherpa mountaineer Tenzing Norgay, who helped make history with the first confirmed ascent of Mount Everest.
  • D. Butwal
    Butwal is a major commercial and transport hub city in southern Nepal, located at the foothills of the Siwalik range.
  • E. Kamtok
    Kamtok is an English-based creole widely used as a lingua franca across Cameroon in informal communication, trade, and popular culture.
  • 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_69c699562484819086752091e3164a27 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c701dd3c808190990e07ced94b3297 completed March 27, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8a229dd348190b9a781b4d34d7b5b completed March 29, 2026, 3:53 a.m.
Created at: March 27, 2026, 4 p.m.