Triple

T3264009
Position Surface form Disambiguated ID Type / Status
Subject Nader Shah E68479 entity
Predicate deathPlace P21 FINISHED
Object Quchan E338360 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: Quchan | Statement: [Nader Shah, deathPlace, Quchan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Quchan
Context triple: [Nader Shah, deathPlace, Quchan]
  • A. Quchan chosen
    Quchan is a historic city in northeastern Iran known for its strategic location along trade routes and its role as a regional center in the Khorasan area.
  • B. Hotan
    Hotan is an oasis city in southwestern Xinjiang, China, historically known as a key Silk Road hub famed for its jade, silk, and carpets.
  • C. Aksu
    Aksu is a city in northwestern China’s Xinjiang Uyghur Autonomous Region, known as an important oasis and agricultural center along the historic Silk Road.
  • D. Korla
    Korla is a major oasis city in Xinjiang, China, known as an important transportation and economic hub along the northern edge of the Taklamakan Desert.
  • E. Karamay
    Karamay is an oil-rich industrial city in northwestern China known for its major petroleum fields and role in the energy industry of Xinjiang.
  • 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_69ad8590444081909e8107a8aeef3a23 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adafaa35e48190b894ca41dd65932b completed March 8, 2026, 5:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69b28ee82a78819082582a24bac97f44 completed March 12, 2026, 10:01 a.m.
Created at: March 8, 2026, 3:09 p.m.