Triple

T7006147
Position Surface form Disambiguated ID Type / Status
Subject Neo-Aramaic languages E162460 entity
Predicate includes P1393 FINISHED
Object Lishanid Noshan E603330 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: Lishanid Noshan | Statement: [Neo-Aramaic languages, includes, Lishanid Noshan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lishanid Noshan
Context triple: [Neo-Aramaic languages, includes, Lishanid Noshan]
  • A. Lishan Didan chosen
    Lishan Didan is a Jewish Neo-Aramaic language traditionally spoken by Kurdish and Azerbaijani Jews from the regions of northwestern Iran and eastern Turkey.
  • B. Yishan
    Yishan was a Qing dynasty military commander and noble who led Chinese forces during the First Opium War against Britain.
  • C. Qishan
    Qishan was a high-ranking Qing dynasty official and diplomat who played a key role in negotiating with the British during the First Opium War.
  • D. Mount Wangwu
    Mount Wangwu is a renowned scenic mountain area in China, celebrated for its dramatic landscapes, cultural legends, and historical significance within the Taihang mountain range.
  • E. Liushi Shan
    Liushi Shan is a prominent high-altitude peak in western China, recognized as the highest summit in the Kunlun Mountains range.
  • 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_69c6885928148190ae31909fbb5e9849 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dc34b5a88190a793e07dd4d0018b completed March 27, 2026, 7:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7755c7c1481908eed49c72726195e completed March 28, 2026, 6:29 a.m.
Created at: March 27, 2026, 2:33 p.m.