Triple
T23506459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Proto-Sinitic |
E572293
|
entity |
| Predicate | ancestorOf |
P369
|
FINISHED |
| Object | Gan Chinese |
—
|
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: Gan Chinese | Statement: [Proto-Sinitic, ancestorOf, Gan Chinese]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gan Chinese Context triple: [Proto-Sinitic, ancestorOf, Gan Chinese]
-
A.
Gan Chinese
chosen
Gan Chinese is a major Sinitic language variety spoken primarily in Jiangxi province and surrounding regions in southeastern China.
-
B.
Hanyu
Hanyu is a Chinese given name shared by various individuals, including notable figures in fields such as acting, sports, and academia.
-
C.
Hán
Hán is the pinyin transcription of the name of the ancient Chinese State of Han, one of the major states during the Warring States period.
-
D.
Xiang Chinese
Xiang Chinese is a major Sinitic language variety spoken primarily in Hunan province and surrounding regions in south-central China.
-
E.
Jin Chinese
Jin Chinese is a major Sinitic language variety spoken primarily in Shanxi and surrounding regions of northern China, often considered distinct from standard Mandarin due to its unique phonological and lexical features.
- 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_69e245b5e4208190bac8a6509867e394 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a9009ca081908c4cffb8c32293ec |
completed | April 29, 2026, 6:45 a.m. |
Created at: April 17, 2026, 6:07 p.m.