Triple

T3849137
Position Surface form Disambiguated ID Type / Status
Subject Burushaski E85247 entity
Predicate spokenIn P2266 FINISHED
Object Hunza Valley E55867 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: Hunza Valley | Statement: [Burushaski, spokenIn, Hunza Valley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hunza Valley
Context triple: [Burushaski, spokenIn, Hunza Valley]
  • A. Hunza Valley chosen
    Hunza Valley is a picturesque mountainous valley in northern Pakistan renowned for its dramatic Karakoram peaks, terraced fields, and traditionally long-lived local communities.
  • B. Parun Valley
    Parun Valley is a remote mountainous valley in eastern Afghanistan’s Nuristan region, known as the homeland of the Prasun-speaking Nuristani people.
  • C. Ghizer Valley
    Ghizer Valley is a scenic mountainous valley in Pakistan’s Gilgit-Baltistan region, known for its rivers, lakes, and trekking routes along the ancient Silk Road corridor.
  • D. Rana valley
    Rana valley is a river valley in the Mo i Rana area of northern Norway, known for its rugged landscapes and surrounding mountains.
  • E. Kaghan Valley
    Kaghan Valley is a scenic alpine valley in northern Pakistan renowned for its lush landscapes, rivers, and popular hill stations that attract tourists year-round.
  • 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_69b5122eb2708190b1aa9da233481015 completed March 14, 2026, 7:45 a.m.
Created at: March 9, 2026, 3:19 p.m.