Triple

T3849161
Position Surface form Disambiguated ID Type / Status
Subject Burushaski E85247 entity
Predicate neighboringLanguage P16383 FINISHED
Object Wakhi E88386 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: Wakhi | Statement: [Burushaski, neighboringLanguage, Wakhi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wakhi
Context triple: [Burushaski, neighboringLanguage, Wakhi]
  • A. Wakhi chosen
    Wakhi is an Eastern Iranian language traditionally spoken by the Wakhi people in the high mountain regions of Pakistan, Afghanistan, Tajikistan, and China.
  • B. Kurmanji
    Kurmanji is the most widely spoken dialect of the Kurdish language, used primarily by Kurds across Turkey, Syria, Iraq, Iran, and the diaspora.
  • C. Brahui
    Brahui is a Dravidian language spoken primarily by the Brahui people in parts of Pakistan, Afghanistan, and Iran.
  • D. Hazara
    Hazara is a mountainous region in northern Pakistan, known for its diverse ethnic communities, strategic location near the Himalayas, and historical significance under various empires and states.
  • E. Khowar
    Khowar is an Indo-Aryan language primarily spoken in the Chitral region of Pakistan and parts of neighboring areas, known for its rich oral tradition and distinct phonology.
  • 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_69aed936de1c81908f91bed80f70abb2 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeebcde86081908cf3840ae002acfa completed March 9, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b504172d58819089d19f5cb7b803ec completed March 14, 2026, 6:45 a.m.
Created at: March 9, 2026, 3:19 p.m.