Triple
T12696298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qiandao Lake |
E303341
|
entity |
| Predicate | ChineseName |
P744
|
FINISHED |
| Object | 千岛湖 |
E303341
|
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: 千岛湖 | Statement: [Qiandao Lake, ChineseName, 千岛湖]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 千岛湖 Context triple: [Qiandao Lake, ChineseName, 千岛湖]
-
A.
Dianshan Lake
Dianshan Lake is a large freshwater lake in Shanghai, China, known as an important water source and popular recreational area.
-
B.
琵琶湖
琵琶湖は滋賀県に位置する日本最大の淡水湖で、多様な生態系と古くからの交通・水資源の要として知られている。
-
C.
本栖湖
本栖湖は、富士五湖の一つとして知られる山梨県の淡水湖で、透明度の高い湖水と富士山を望む景観で有名な観光地です。
-
D.
Qiandao Lake
chosen
Qiandao Lake is a large, man-made reservoir in eastern China famed for its thousands of forested islands, clear waters, and popular tourist and recreation areas.
-
E.
慈湖
慈湖 is a scenic lake in Taiwan known for its tranquil natural surroundings and historical significance as the site of the Cihu Mausoleum of former President Chiang Kai-shek.
- 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_69d7bdef90d48190b46b88270e780946 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961ebd17081909f983567e4b36533 |
completed | April 10, 2026, 8:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f671ae935c8190a7fc2cf3c0987248 |
completed | May 2, 2026, 9:50 p.m. |
Created at: April 9, 2026, 5:22 p.m.