Triple

T14578122
Position Surface form Disambiguated ID Type / Status
Subject Tieshangang District E342111 entity
Predicate locatedIn P40 FINISHED
Object Beihai E56871 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: Beihai | Statement: [Tieshangang District, locatedIn, Beihai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beihai
Context triple: [Tieshangang District, locatedIn, Beihai]
  • A. Beihai chosen
    Beihai is a coastal city in China's Guangxi Zhuang Autonomous Region, known for its beaches, maritime trade, and the scenic Silver Beach tourist area.
  • B. Beihai Port
    Beihai Port is a major seaport on the southern coast of China that serves as an important maritime gateway for trade in the Beibu Gulf region.
  • C. Beibu Wan
    Beibu Wan is the Chinese name for the Gulf of Tonkin, a large body of water in the South China Sea bordered by China and Vietnam.
  • D. Wanning
    Wanning is a county-level coastal city in southeastern Hainan, China, known for its tropical climate, beaches, and surf-friendly bays.
  • E. Shekou
    Shekou is a coastal district in Shenzhen, China, known as a major transportation and commercial hub with significant port facilities and expatriate communities.
  • 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_69d822dcc6248190bed689984bceb0e2 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb3f5ec448190b2ef887fdf7b633e completed April 14, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd8ad03e7881908a783182c6d656b5 completed May 8, 2026, 7:03 a.m.
Created at: April 10, 2026, 1:24 a.m.