Triple
T18760457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henan University |
E458756
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Kaifeng |
—
|
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: Kaifeng | Statement: [Henan University, locatedIn, Kaifeng]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kaifeng Context triple: [Henan University, locatedIn, Kaifeng]
-
A.
Kaifeng
chosen
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.
-
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.
Zhoukou
Zhoukou is a prefecture-level city in eastern Henan Province, China, known as an important agricultural and transportation hub with historical and cultural significance.
-
D.
Zhengzhou
Zhengzhou is a major city in central China that serves as the capital of Henan Province and an important national transportation and industrial hub.
-
E.
Nanzheng
Nanzheng is the historical name of Hanzhong, an ancient city in southwestern Shaanxi, China, known for its strategic location and rich cultural heritage.
- 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_69d8d395dba0819087568404508590cb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e58d7ecca881909d6c262837b621b3 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 10, 2026, 11:52 a.m.