Triple

T7439460
Position Surface form Disambiguated ID Type / Status
Subject Weifang E171707 entity
Predicate borders P224 FINISHED
Object Linyi E176007 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: Linyi | Statement: [Weifang, borders, Linyi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Linyi
Context triple: [Weifang, borders, Linyi]
  • A. Linyi chosen
    Linyi is a major prefecture-level city in southeastern Shandong Province, China, known for its large population, historical significance, and role as a regional commercial and logistics hub.
  • B. Jining
    Jining is a city in Shandong Province, China, historically significant as a transport and commercial hub along the Grand Canal.
  • C. Rizhao
    Rizhao is a coastal city in eastern China known for its sunny climate, beaches, and port on the Yellow Sea.
  • D. Zibo
    Zibo is an industrial and historical city in eastern China known for its ceramics, petrochemical industry, and role as a former capital of the ancient State of Qi.
  • E. Binzhou
    Binzhou is a prefecture-level city in northern Shandong Province, China, located near the lower reaches of the Yellow River and known for its developing industrial and agricultural economy.
  • 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_69c68a64228c8190affaec2a8127ce7b completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f34c28648190a426b5d7623b41e8 completed March 27, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69c84ee844cc819081f44426658c7e27 completed March 28, 2026, 9:58 p.m.
Created at: March 27, 2026, 3:13 p.m.