Triple
T22402953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qingdao University |
E553805
|
entity |
| Predicate | province |
P604
|
FINISHED |
| Object | Shandong |
—
|
NE NERFINISHED |
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: [Qingdao University, province, Shandong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shandong Context triple: [Qingdao University, province, 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 (2 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_69e11e4da7048190b4387d422a9a0de5 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f158b565c48190b0f6c19f17995b40 |
completed | April 29, 2026, 1:02 a.m. |
Created at: April 16, 2026, 8:46 p.m.