Triple

T5459929
Position Surface form Disambiguated ID Type / Status
Subject Serindia E122570 entity
Predicate subject P450 FINISHED
Object Turfan E132166 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: Turfan | Statement: [Serindia, subject, Turfan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Turfan
Context triple: [Serindia, subject, Turfan]
  • A. Turpan chosen
    Turpan is an oasis city and depression in China’s Xinjiang region, historically a key Silk Road hub known for its extreme heat, ancient irrigation systems, and grape cultivation.
  • B. Quchan
    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.
  • C. 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.
  • 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. Kashgar
    Kashgar is an ancient oasis city in western China’s Xinjiang region that long served as a key cultural and commercial crossroads between East and West.
  • 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_69bd46424248819085282ddf50a565f3 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd91f353c481909ae1a73ae419fb9a completed March 20, 2026, 6:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf488866088190b213bd641f8b247c completed March 22, 2026, 1:40 a.m.
Created at: March 20, 2026, 2:08 p.m.