Triple

T12337144
Position Surface form Disambiguated ID Type / Status
Subject Mao River E294116 entity
Predicate flowsThrough P225 FINISHED
Object Shanghai E5256 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: Shanghai | Statement: [Mao River, flowsThrough, Shanghai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shanghai
Context triple: [Mao River, flowsThrough, Shanghai]
  • A. Shanghai chosen
    Shanghai is a major global financial hub and China’s largest city, known for its modern skyline, historic waterfront, and role as a center of international business and trade.
  • B. Shanghai
    Shanghai is an unincorporated community located in Berkeley County, West Virginia, United States.
  • C. Shanghai
    Shanghai is a major Ethereum network upgrade that introduced key changes such as enabling staked ETH withdrawals and improving the protocol’s efficiency and flexibility.
  • D. Beijing
    Beijing is the capital city of China, a major political, cultural, and economic center known for its rich history and rapid modern development.
  • E. Tianjin
    Tianjin is a major port city and industrial hub in northern China, located near Beijing along the Bohai Sea.
  • 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_69d6ab6ae0dc8190b1522a9c1c55c114 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f6683e881908920e1fee02a14e3 completed April 10, 2026, 6:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6346c06208190b4e39fcbdb6a06fa completed May 2, 2026, 5:29 p.m.
Created at: April 8, 2026, 9:53 p.m.