Triple

T8258658
Position Surface form Disambiguated ID Type / Status
Subject Tongji-German College alliances E193134 entity
Predicate geographicScope P82 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: [Tongji-German College alliances, geographicScope, Shanghai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shanghai
Context triple: [Tongji-German College alliances, geographicScope, 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 a major Ethereum network upgrade that introduced key changes such as enabling staked ETH withdrawals and improving the protocol’s efficiency and flexibility.
  • C. Beijing
    Beijing is the capital city of China, a major political, cultural, and economic center known for its rich history and rapid modern development.
  • D. Tianjin
    Tianjin is a major port city and industrial hub in northern China, located near Beijing along the Bohai Sea.
  • E. Guangzhou
    Guangzhou is a major port city in southern China and the capital of Guangdong Province, known as a key commercial and manufacturing hub in the Pearl River Delta.
  • 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_69ca82dfad9c8190b8cd18fb89f50f40 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb78fe5e2c819080741ea24bae0807 completed March 31, 2026, 7:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd947cf7a881908b45cf262887da86 completed April 1, 2026, 9:56 p.m.
Created at: March 30, 2026, 5:49 p.m.