Triple

T17124643
Position Surface form Disambiguated ID Type / Status
Subject Menglianggu Campaign E415560 entity
Predicate location P40 FINISHED
Object Shandong E12524 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: Shandong | Statement: [Menglianggu Campaign, location, Shandong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shandong
Context triple: [Menglianggu Campaign, location, Shandong]
  • A. Shandong chosen
    Shandong is a coastal province in eastern China that has historically been a significant political, military, and cultural center, notably during various conflicts in modern Chinese history.
  • B. Liaoning
    Liaoning is a northeastern coastal province of China known for its heavy industry, port cities, and role as a gateway to the Korean Peninsula.
  • C. Kiaochow
    Kiaochow is the former German colonial name for the Chinese port city now known as Qingdao on the Shandong Peninsula.
  • D. Hebei
    Hebei is a northern Chinese province surrounding Beijing and Tianjin, historically significant as a major political, military, and industrial region.
  • E. Jiangsu
    Jiangsu is a populous and economically significant coastal province in eastern China, known for its rich history, dense urbanization, and major cities such as Nanjing and Suzhou.
  • 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_69d886d090cc8190a39cb94992586905 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f025fce481908e261f2e363e14f9 completed April 18, 2026, 8:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a013a12a7288190911c1be2667916c0 completed May 11, 2026, 2:08 a.m.
Created at: April 10, 2026, 5:36 a.m.