Triple

T2938407
Position Surface form Disambiguated ID Type / Status
Subject Mukden Incident E79325 entity
Predicate location P40 FINISHED
Object Liaoning Province E71823 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: Liaoning Province | Statement: [Mukden Incident, location, Liaoning Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Liaoning Province
Context triple: [Mukden Incident, location, Liaoning Province]
  • A. Liaoning chosen
    Liaoning is a northeastern coastal province of China known for its heavy industry, port cities, and role as a gateway to the Korean Peninsula.
  • B. Jilin Province
    Jilin Province is a northeastern Chinese province in the historical region of Manchuria, known for its cold climate, heavy industry, and significant Korean ethnic minority.
  • C. Shandong
    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.
  • D. Hebei
    Hebei is a northern Chinese province surrounding Beijing and Tianjin, historically significant as a major political, military, and industrial region.
  • E. Heilongjiang
    Heilongjiang is a northeastern Chinese province known for its cold climate, heavy industry, and border with Russia.
  • 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_69ad8b0fbab081908f6a61567c045d8d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad986c1c0c8190a6a9f17082438cfd completed March 8, 2026, 3:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69b086837ddc8190af27c7facd629691 completed March 10, 2026, 9 p.m.
Created at: March 8, 2026, 2:56 p.m.