Triple
T2708606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xuzhou |
E59803
|
entity |
| Predicate | formerName |
P65
|
FINISHED |
| Object |
Pengcheng
Pengcheng is the historical name of the ancient Chinese city that later became known as Xuzhou, an important regional center in eastern China.
|
E294991
|
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: Pengcheng | Statement: [Xuzhou, formerName, Pengcheng]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pengcheng Context triple: [Xuzhou, formerName, Pengcheng]
-
A.
Xinzhuang
Xinzhuang is a major suburban town and transportation hub in Shanghai, China, known for its busy commercial areas and key metro and rail connections.
-
B.
Putian
Putian is a coastal prefecture-level city in southeastern China known for its manufacturing industries, especially footwear, and its historical and cultural heritage within Fujian province.
-
C.
Ruchang
Ruchang is a Chinese given name most notably borne by Ding Ruchang, a late Qing dynasty naval commander.
-
D.
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.
-
E.
Jianye
Jianye is an ancient name for the city now known as Nanjing, a historically significant capital in several Chinese dynasties.
- 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: Pengcheng Triple: [Xuzhou, formerName, Pengcheng]
Generated description
Pengcheng is the historical name of the ancient Chinese city that later became known as Xuzhou, an important regional center in eastern China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pengcheng Target entity description: Pengcheng is the historical name of the ancient Chinese city that later became known as Xuzhou, an important regional center in eastern China.
-
A.
Xinzhuang
Xinzhuang is a major suburban town and transportation hub in Shanghai, China, known for its busy commercial areas and key metro and rail connections.
-
B.
Putian
Putian is a coastal prefecture-level city in southeastern China known for its manufacturing industries, especially footwear, and its historical and cultural heritage within Fujian province.
-
C.
Ruchang
Ruchang is a Chinese given name most notably borne by Ding Ruchang, a late Qing dynasty naval commander.
-
D.
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.
-
E.
Jianye
Jianye is an ancient name for the city now known as Nanjing, a historically significant capital in several Chinese dynasties.
- 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_69ab4ac92a088190bc74bca14038e3de |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda7542548190bbf6c947145f7f63 |
completed | March 7, 2026, 7:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afbbbc2eec819082f6e6e157d4efc7 |
completed | March 10, 2026, 6:35 a.m. |
| NEDg | Description generation | batch_69afbc67c39c8190b5932c0e23595f64 |
completed | March 10, 2026, 6:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afbd2d8a2c8190896a9154ebbd8bab |
completed | March 10, 2026, 6:41 a.m. |
Created at: March 6, 2026, 9:55 p.m.