Triple
T21943039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xinhui |
E541867
|
entity |
| Predicate | hasNotableTown |
P14082
|
FINISHED |
| Object |
Liangxi
Liangxi is a notable town within Xinhui District in Jiangmen, Guangdong Province, China.
|
E1508889
|
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: Liangxi | Statement: [Xinhui, hasNotableTown, Liangxi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Liangxi Context triple: [Xinhui, hasNotableTown, Liangxi]
-
A.
Lianghe
Lianghe is a town in southwestern China's Yunnan province, known as the seat of Lianghe County within the Dehong Dai and Jingpo Autonomous Prefecture.
-
B.
Houtong
Houtong is a small village in New Taipei, Taiwan, best known for its former coal-mining industry and its popular cat-themed tourism.
-
C.
Liangxiang
Liangxiang is a historic town in Beijing’s Fangshan District known for its ancient architecture and cultural heritage.
-
D.
Liuhe
Liuhe is a town in Taicang, Jiangsu Province, China, known as a local residential and educational hub within the greater Suzhou region.
-
E.
Nanxi
Nanxi was an early form of Chinese drama from the Song dynasty that combined music, dialogue, and dance, and is considered a foundational precursor to later Chinese operatic traditions.
- 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: Liangxi Triple: [Xinhui, hasNotableTown, Liangxi]
Generated description
Liangxi is a notable town within Xinhui District in Jiangmen, Guangdong Province, China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Liangxi Target entity description: Liangxi is a notable town within Xinhui District in Jiangmen, Guangdong Province, China.
-
A.
Lianghe
Lianghe is a town in southwestern China's Yunnan province, known as the seat of Lianghe County within the Dehong Dai and Jingpo Autonomous Prefecture.
-
B.
Houtong
Houtong is a small village in New Taipei, Taiwan, best known for its former coal-mining industry and its popular cat-themed tourism.
-
C.
Liangxiang
Liangxiang is a historic town in Beijing’s Fangshan District known for its ancient architecture and cultural heritage.
-
D.
Liuhe
Liuhe is a town in Taicang, Jiangsu Province, China, known as a local residential and educational hub within the greater Suzhou region.
-
E.
Nanxi
Nanxi was an early form of Chinese drama from the Song dynasty that combined music, dialogue, and dance, and is considered a foundational precursor to later Chinese operatic traditions.
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1242515ec8190b015bf8c7b13be85 |
completed | April 28, 2026, 9:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a60ee7cc48190bf32574b758c6425 |
completed | May 18, 2026, 12:44 a.m. |
| NEDg | Description generation | batch_6a0a6170bc5c8190b6b28e02675da476 |
completed | May 18, 2026, 12:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a61f66a988190b07a9e36cacf44bf |
completed | May 18, 2026, 12:48 a.m. |
Created at: April 16, 2026, 7:56 p.m.