Triple
T21943258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guangyun |
E541872
|
entity |
| Predicate | relatedWork |
P37
|
FINISHED |
| Object | Jiyun |
—
|
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: Jiyun | Statement: [Guangyun, relatedWork, Jiyun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jiyun Context triple: [Guangyun, relatedWork, Jiyun]
-
A.
Jiyun
chosen
Jiyun is an 11th-century Chinese rime dictionary that systematically records and organizes the phonology and characters of Middle Chinese.
-
B.
Jinyu
Jinyu is a major variety of the Jin group of Chinese dialects spoken primarily in northern China, especially in Shanxi and surrounding regions.
-
C.
Juyi
Juyi is the given name of Bai Juyi, a renowned Tang dynasty Chinese poet celebrated for his accessible style and social commentary.
-
D.
Jiyao
Jiyao is a given name most notably associated with Tang Jiyao, a prominent Chinese warlord and political figure of the early 20th century.
-
E.
Jung-Wien
Jung-Wien was a late 19th-century Viennese literary circle of young modernist writers and critics, including figures like Hugo von Hofmannsthal, that helped shape Austrian literature and culture.
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1242515ec8190b015bf8c7b13be85 |
completed | April 28, 2026, 9:18 p.m. |
Created at: April 16, 2026, 7:56 p.m.