Triple

T13851118
Position Surface form Disambiguated ID Type / Status
Subject Shuozhou E332942 entity
Predicate romanization P2508 FINISHED
Object Shuòzhōu E332942 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: Shuòzhōu | Statement: [Shuozhou, romanization, Shuòzhōu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shuòzhōu
Context triple: [Shuozhou, romanization, Shuòzhōu]
  • A. Shuozhou chosen
    Shuozhou is a prefecture-level city in northern China known for its coal resources and historical sites within Shanxi Province.
  • B. Wuzhong
    Wuzhong is a prefecture-level city in central Ningxia, China, known for its significant Hui Muslim population and its role as an agricultural and transport hub along the Yellow River.
  • C. Lüliang
    Lüliang is a prefecture-level city in western Shanxi Province, China, known for its mountainous terrain and significant coal and energy resources.
  • D. Shanxi Province
    Shanxi Province is a landlocked region in northern China known for its rich coal resources, well-preserved ancient architecture, and significant historical and cultural heritage.
  • E. Shàoyáng
    Shàoyáng is a prefecture-level city in southwestern Hunan Province, China, known for its long history, diverse ethnic culture, and role as a regional transportation and commercial hub.
  • 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_69d81c5ba13c8190839315f54768acfd completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02d8fb788190baef7537be2baecb completed April 14, 2026, 9:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c0f73838819085d6f052c00fc494 completed May 3, 2026, 9:41 p.m.
Created at: April 9, 2026, 10:14 p.m.