Triple

T3308633
Position Surface form Disambiguated ID Type / Status
Subject Liang Xiaosheng E69513 entity
Predicate placeOfBirth P1 FINISHED
Object Harbin E180578 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: Harbin | Statement: [Liang Xiaosheng, placeOfBirth, Harbin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harbin
Context triple: [Liang Xiaosheng, placeOfBirth, Harbin]
  • A. Harbin chosen
    Harbin is a major city in northeastern China known for its Russian-influenced architecture and its internationally famous annual ice and snow festival.
  • B. Qiqihar
    Qiqihar is a major industrial city in northeastern China’s Heilongjiang province, known historically as a regional transportation hub and center for heavy industry.
  • C. Dalian
    Dalian is a major port city in northeastern China known for its strategic location on the Liaodong Peninsula, maritime trade, and modern urban development.
  • D. Changchun
    Changchun is a major city in northeastern China that served as the capital of the Japanese puppet state of Manchukuo during the early 20th century.
  • E. Shenyang
    Shenyang is a major industrial and historical city in northeastern China and the capital of Liaoning Province.
  • 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_69ad859f218081909458d2cebbf57565 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb0e9f33c81909cff835a83e0a657 completed March 8, 2026, 5:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69b34bb5d0b88190b1895fd352924862 completed March 12, 2026, 11:26 p.m.
Created at: March 8, 2026, 3:11 p.m.