Triple
T19321173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhouzhuang |
E483226
|
entity |
| Predicate | hasRiver |
P165
|
FINISHED |
| Object | Nanhu Lake |
—
|
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: Nanhu Lake | Statement: [Zhouzhuang, hasRiver, Nanhu Lake]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nanhu Lake Context triple: [Zhouzhuang, hasRiver, Nanhu Lake]
-
A.
Nanhu Lake
chosen
Nanhu Lake is a historic scenic lake in Jiaxing, Zhejiang, best known as the site of the First National Congress of the Chinese Communist Party held on a boat on its waters.
-
B.
Donghu Lake
Donghu Lake is a large scenic freshwater lake in Wuhan, China, renowned for its parks, cultural sites, and recreational areas.
-
C.
Zhonghai lake
Zhonghai Lake is a central body of water within Beijing’s Zhongnanhai leadership compound, situated adjacent to the core of China’s central government.
-
D.
Yanhu Lake
Yanhu Lake is a scenic mountain lake nestled within China’s Yandang Mountains, known for its picturesque landscapes and tranquil natural setting.
-
E.
Liangzi Lake
Liangzi Lake is a large freshwater lake in Hubei Province, China, known for its rich biodiversity and important role in local fisheries and ecology.
- 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_69d8e8d13e3c81909d91d1d5ec37c095 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e60d88951081909f7ce6e0610c7258 |
completed | April 20, 2026, 11:27 a.m. |
Created at: April 10, 2026, 1:32 p.m.