Triple

T6647257
Position Surface form Disambiguated ID Type / Status
Subject Chevrolet Onix E150732 entity
Predicate assemblyLocation P40 FINISHED
Object Liuzhou, China E25569 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: Liuzhou, China | Statement: [Chevrolet Onix, assemblyLocation, Liuzhou, China]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Liuzhou, China
Context triple: [Chevrolet Onix, assemblyLocation, Liuzhou, China]
  • A. Liuzhou, Guangxi, China chosen
    Liuzhou is an industrial city in the Guangxi Zhuang Autonomous Region of southern China, known for its major automotive manufacturing sector and role as a regional transportation hub.
  • B. Liuzhou
    Liuzhou is a major industrial city in the Guangxi Zhuang Autonomous Region of southern China, known for its heavy industry, transportation hub status, and distinctive karst landscape.
  • C. Wuzhou
    Wuzhou is a prefecture-level city in eastern Guangxi, China, known as a regional transport hub and commercial center along the Xi River.
  • D. Guigang
    Guigang is a prefecture-level city in southeastern Guangxi, China, known as a regional transport hub and commercial center along the Xun River.
  • E. Wuzhou Wu
    Wuzhou Wu is a regional variety of the Wu group of Chinese dialects spoken in and around Wuzhou.
  • 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_69c687f1a3048190828b7342f7125d5c completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b01eb9148190a3f462e57c7556c2 completed March 27, 2026, 4:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69c72f79fa7c81909904de229cb4ed50 completed March 28, 2026, 1:31 a.m.
Created at: March 27, 2026, 2 p.m.