Triple
T13341283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ningbonese |
E317828
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object |
Ningbohua
Ningbohua is a Chinese Wu dialect spoken primarily in and around the city of Ningbo in Zhejiang province.
|
E1034593
|
NE FINISHED |
How this triple was built (4 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: Ningbohua | Statement: [Ningbonese, hasAlternativeName, Ningbohua]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ningbohua Context triple: [Ningbonese, hasAlternativeName, Ningbohua]
-
A.
Hangzhouhua
Hangzhouhua is a regional Chinese dialect spoken in and around the city of Hangzhou in Zhejiang province.
-
B.
Bianliang
Bianliang is the historical name of the Chinese city that served as the capital during the Northern Song dynasty, now known as Kaifeng.
-
C.
Shanghai Chenghuang Miao
Shanghai Chenghuang Miao is a historic Taoist temple and popular cultural landmark in Shanghai, renowned for its traditional architecture, religious significance, and bustling surrounding marketplace.
-
D.
Huaxiang
Huaxiang is a subdistrict-level area within Beijing’s Fengtai District, known primarily as a residential and urban community zone.
-
E.
Qibao
Qibao is an ancient water town and popular tourist area in Shanghai, known for its historic streets, canals, and traditional architecture.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ningbohua Triple: [Ningbonese, hasAlternativeName, Ningbohua]
Generated description
Ningbohua is a Chinese Wu dialect spoken primarily in and around the city of Ningbo in Zhejiang province.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ningbohua Target entity description: Ningbohua is a Chinese Wu dialect spoken primarily in and around the city of Ningbo in Zhejiang province.
-
A.
Hangzhouhua
Hangzhouhua is a regional Chinese dialect spoken in and around the city of Hangzhou in Zhejiang province.
-
B.
Bianliang
Bianliang is the historical name of the Chinese city that served as the capital during the Northern Song dynasty, now known as Kaifeng.
-
C.
Shanghai Chenghuang Miao
Shanghai Chenghuang Miao is a historic Taoist temple and popular cultural landmark in Shanghai, renowned for its traditional architecture, religious significance, and bustling surrounding marketplace.
-
D.
Huaxiang
Huaxiang is a subdistrict-level area within Beijing’s Fengtai District, known primarily as a residential and urban community zone.
-
E.
Qibao
Qibao is an ancient water town and popular tourist area in Shanghai, known for its historic streets, canals, and traditional architecture.
- F. None of above. chosen
Provenance (5 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99d0379d481909a50fff31b19fed1 |
completed | April 11, 2026, 12:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f71f3ecf4c8190bb9eee699859dc08 |
completed | May 3, 2026, 10:11 a.m. |
| NEDg | Description generation | batch_69f72018c4848190941732e3a938278a |
completed | May 3, 2026, 10:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f720bf04548190833af70061b017a1 |
completed | May 3, 2026, 10:17 a.m. |
Created at: April 9, 2026, 9:31 p.m.