Triple
T2991016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jinan |
E80751
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object |
Tsinan
Tsinan is an older romanized name for Jinan, the capital city of Shandong Province in eastern China known for its numerous natural springs.
|
E317302
|
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: Tsinan | Statement: [Jinan, hasAlternativeName, Tsinan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tsinan Context triple: [Jinan, hasAlternativeName, Tsinan]
-
A.
Jinling
Jinling is an ancient name for the Chinese city now known as Nanjing, historically renowned as a major political and cultural center.
-
B.
Chongxin
Chongxin is the Chinese given name of Joe Tsai, the Taiwanese-Canadian co-founder and executive vice chairman of Alibaba Group.
-
C.
Tianhe
Tianhe is the core module of China’s Tiangong space station, serving as its main control, living, and docking hub in low Earth orbit.
-
D.
Tianhe
Tianhe is a town in Wuhan, Hubei Province, China, best known for hosting Wuhan Tianhe International Airport, a major air transport hub in central China.
-
E.
Tsien
Tsien is a Chinese surname borne by several notable figures in science and engineering, including biophysicist Richard Tsien.
- 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: Tsinan Triple: [Jinan, hasAlternativeName, Tsinan]
Generated description
Tsinan is an older romanized name for Jinan, the capital city of Shandong Province in eastern China known for its numerous natural springs.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tsinan Target entity description: Tsinan is an older romanized name for Jinan, the capital city of Shandong Province in eastern China known for its numerous natural springs.
-
A.
Jinling
Jinling is an ancient name for the Chinese city now known as Nanjing, historically renowned as a major political and cultural center.
-
B.
Chongxin
Chongxin is the Chinese given name of Joe Tsai, the Taiwanese-Canadian co-founder and executive vice chairman of Alibaba Group.
-
C.
Tianhe
Tianhe is the core module of China’s Tiangong space station, serving as its main control, living, and docking hub in low Earth orbit.
-
D.
Tianhe
Tianhe is a town in Wuhan, Hubei Province, China, best known for hosting Wuhan Tianhe International Airport, a major air transport hub in central China.
-
E.
Tsien
Tsien is a Chinese surname borne by several notable figures in science and engineering, including biophysicist Richard Tsien.
- 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_69ad8b16c3488190b47b6aa7a59a335b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99de55208190bc56ecbe08638e5a |
completed | March 8, 2026, 3:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b109039cfc8190a286c83df752967e |
completed | March 11, 2026, 6:17 a.m. |
| NEDg | Description generation | batch_69b10bc71c708190b1e620d41278c3e0 |
completed | March 11, 2026, 6:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b10c43a7c48190b63a7b3f0f180d44 |
completed | March 11, 2026, 6:31 a.m. |
Created at: March 8, 2026, 2:59 p.m.