Triple
T1617112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waterloo, Ontario |
E34744
|
entity |
| Predicate | hasSisterCity |
P919
|
FINISHED |
| Object | Zhengzhou |
E125528
|
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: Zhengzhou | Statement: [Waterloo, Ontario, hasSisterCity, Zhengzhou]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zhengzhou Context triple: [Waterloo, Ontario, hasSisterCity, Zhengzhou]
-
A.
Zhengzhou
chosen
Zhengzhou is a major city in central China that serves as the capital of Henan Province and an important national transportation and industrial hub.
-
B.
Luoyang
Luoyang is one of China’s oldest and most historically significant cities, renowned as an ancient imperial capital and cultural center along the Yellow River.
-
C.
Kaifeng
Kaifeng is an ancient city in eastern Henan, China, historically significant as a former capital of several Chinese dynasties and a major cultural and economic center.
-
D.
Liuyang
Liuyang is a county-level city in Hunan Province, China, known for its fireworks industry and cultural heritage.
-
E.
Bozhou
Bozhou is a historic city in northern Anhui Province, China, known as a major center of traditional Chinese medicine and ancient culture.
- 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_69a885ffc5ec819091afa325d5f9611c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a909abbec081908f95547471530ad5 |
completed | March 5, 2026, 4:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ada96dc52c8190be0ace80c5eb4cf3 |
completed | March 8, 2026, 4:53 p.m. |
Created at: March 4, 2026, 7:28 p.m.