Triple
T1080201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Republic of China |
E23926
|
entity |
| Predicate | previousCapital |
P3417
|
FINISHED |
| Object | Chongqing |
E36590
|
NE FINISHED |
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: Chongqing | Statement: [Republic of China, previousCapital, Chongqing]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chongqing Context triple: [Republic of China, previousCapital, Chongqing]
-
A.
Chongqing
chosen
Chongqing is a vast inland metropolis in southwestern China known for its steep hilly terrain, spicy hotpot cuisine, and role as a major industrial and transportation hub along the upper Yangtze River.
-
B.
Wuhan
Wuhan is a major city in central China, known as a key industrial, commercial, and transportation hub located at the confluence of the Yangtze and Han rivers.
-
C.
Luzhou
Luzhou is an old historical name for the city now known as Hefei, the capital of Anhui Province in eastern China.
-
D.
Shanghai
Shanghai is a major global financial hub and China’s largest city, known for its modern skyline, historic waterfront, and role as a center of international business and trade.
-
E.
Tianjin
Tianjin is a major port city and industrial hub in northern China, located near Beijing along the Bohai Sea.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a493f1ddf48190a99d54b00e99f8ce |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b94509d08190964509ea4a2d7912 |
completed | March 1, 2026, 10:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adc977276881908405e2411eb14fa1 |
completed | March 8, 2026, 7:09 p.m. |
Created at: March 1, 2026, 7:42 p.m.