Triple
T1743083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yunnan Province |
E38274
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Yuxi
Yuxi is a prefecture-level city in central Yunnan Province, China, known for its tobacco production and scenic plateau lake landscapes.
|
E204312
|
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: Yuxi | Statement: [Yunnan Province, containsCity, Yuxi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yuxi Context triple: [Yunnan Province, containsCity, Yuxi]
-
A.
Kunming, China
Kunming, China is a major city in southwest China that served as a key World War II air base and supply hub, notably for the American Volunteer Group known as the Flying Tigers.
-
B.
Pu'er
Pu'er is a city in southwestern China best known as the namesake and historic production center of Pu'er tea.
-
C.
Guiyang
Guiyang is the capital city of Guizhou Province in southwest China, known for its cool climate, karst landscapes, and role as a regional transportation and industrial hub.
-
D.
Luzhou
Luzhou is an old historical name for the city now known as Hefei, the capital of Anhui Province in eastern China.
-
E.
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.
- 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: Yuxi Triple: [Yunnan Province, containsCity, Yuxi]
Generated description
Yuxi is a prefecture-level city in central Yunnan Province, China, known for its tobacco production and scenic plateau lake landscapes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Yuxi Target entity description: Yuxi is a prefecture-level city in central Yunnan Province, China, known for its tobacco production and scenic plateau lake landscapes.
-
A.
Kunming, China
Kunming, China is a major city in southwest China that served as a key World War II air base and supply hub, notably for the American Volunteer Group known as the Flying Tigers.
-
B.
Pu'er
Pu'er is a city in southwestern China best known as the namesake and historic production center of Pu'er tea.
-
C.
Guiyang
Guiyang is the capital city of Guizhou Province in southwest China, known for its cool climate, karst landscapes, and role as a regional transportation and industrial hub.
-
D.
Luzhou
Luzhou is an old historical name for the city now known as Hefei, the capital of Anhui Province in eastern China.
-
E.
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.
- 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_69adbf4ba8fc81909b538168a4403330 |
completed | March 8, 2026, 6:26 p.m. |
| NEDg | Description generation | batch_69adc2b4d8a0819080ff41cf73417276 |
completed | March 8, 2026, 6:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adc38732d8819092e0ac76354f08c1 |
completed | March 8, 2026, 6:44 p.m. |
Created at: March 4, 2026, 7:31 p.m.