Triple
T1743091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yunnan Province |
E38274
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Lincang
Lincang is a prefecture-level city in southwestern China known for its tea production, diverse ethnic cultures, and location near the border with Myanmar.
|
E230320
|
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: Lincang | Statement: [Yunnan Province, containsCity, Lincang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lincang Context triple: [Yunnan Province, containsCity, Lincang]
-
A.
Lingang
Lingang is a rapidly developing industrial and high-tech district in Shanghai, China, known for hosting major manufacturing facilities such as Tesla’s Gigafactory Shanghai.
-
B.
Xiantao
Xiantao is a county-level city in central China’s Hubei province, known for its location on the Jianghan Plain and its role as a regional agricultural and industrial center.
-
C.
Jinqiao
Jinqiao is a subdistrict in Shanghai’s Pudong New Area known for its residential communities and growing commercial and industrial zones.
-
D.
Jianye
Jianye is an ancient name for the city now known as Nanjing, a historically significant capital in several Chinese dynasties.
-
E.
Shíyàn
Shíyàn is the Hanyu Pinyin romanization of the Chinese city name Shiyan, located in Hubei Province, China.
- 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: Lincang Triple: [Yunnan Province, containsCity, Lincang]
Generated description
Lincang is a prefecture-level city in southwestern China known for its tea production, diverse ethnic cultures, and location near the border with Myanmar.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lincang Target entity description: Lincang is a prefecture-level city in southwestern China known for its tea production, diverse ethnic cultures, and location near the border with Myanmar.
-
A.
Lingang
Lingang is a rapidly developing industrial and high-tech district in Shanghai, China, known for hosting major manufacturing facilities such as Tesla’s Gigafactory Shanghai.
-
B.
Xiantao
Xiantao is a county-level city in central China’s Hubei province, known for its location on the Jianghan Plain and its role as a regional agricultural and industrial center.
-
C.
Jinqiao
Jinqiao is a subdistrict in Shanghai’s Pudong New Area known for its residential communities and growing commercial and industrial zones.
-
D.
Jianye
Jianye is an ancient name for the city now known as Nanjing, a historically significant capital in several Chinese dynasties.
-
E.
Shíyàn
Shíyàn is the Hanyu Pinyin romanization of the Chinese city name Shiyan, located in Hubei Province, China.
- 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_69a8862b01a48190ab47209063af82d9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa63c836d48190bd44ea24977aba2d |
completed | March 6, 2026, 5:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae26ee4c088190a767d71f1a68a734 |
completed | March 9, 2026, 1:48 a.m. |
| NEDg | Description generation | batch_69ae277895488190ae4a2337cf2ae915 |
completed | March 9, 2026, 1:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae27e7113081909835657bfff3f9e8 |
completed | March 9, 2026, 1:52 a.m. |
Created at: March 4, 2026, 7:31 p.m.