Triple
T14796204
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sayama |
E347782
|
entity |
| Predicate | hasSisterCity |
P919
|
FINISHED |
| Object | Hangzhou, China |
E66170
|
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: Hangzhou, China | Statement: [Sayama, hasSisterCity, Hangzhou, China]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hangzhou, China Context triple: [Sayama, hasSisterCity, Hangzhou, China]
-
A.
Hangzhou
chosen
Hangzhou is a major city in eastern China renowned for its historic West Lake, rich cultural heritage, and role as a key economic and technological hub in the Yangtze River Delta region.
-
B.
Ningbo, China
Ningbo, China is a major port city in eastern Zhejiang province known for its long maritime history and role as a key hub in regional and international trade.
-
C.
Xihu District, Hangzhou
Xihu District, Hangzhou is a central urban district of Hangzhou, China, famed for encompassing the scenic West Lake area and several major cultural and natural attractions.
-
D.
Hangzhouhua
Hangzhouhua is a regional Chinese dialect spoken in and around the city of Hangzhou in Zhejiang province.
-
E.
Hsiangcheng, China
Hsiangcheng, China is a town in Henan Province known as the birthplace of author and social critic Os Guinness.
- 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_69d822ea8b7c819097dfadf3d45545e6 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decd5fdd548190a2ee5e668c2b20b4 |
completed | April 14, 2026, 11:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe24c0beb0819081a124479a849bb6 |
completed | May 8, 2026, 6 p.m. |
Created at: April 10, 2026, 1:31 a.m.