Triple
T11245973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 帝国大学 |
E266204
|
entity |
| Predicate | includes |
P1393
|
FINISHED |
| Object |
台北帝国大学
台北帝国大学 was a Japanese colonial-era imperial university in Taipei that later became the foundation for National Taiwan University.
|
E913640
|
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: 台北帝国大学 | Statement: [帝国大学, includes, 台北帝国大学]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 台北帝国大学 Context triple: [帝国大学, includes, 台北帝国大学]
-
A.
國學院大學
國學院大學 is a private Japanese university in Tokyo known for its focus on Shinto studies, Japanese history, and traditional culture.
-
B.
National Yang-Ming University
National Yang-Ming University was a leading Taiwanese research university renowned for its strengths in medicine, life sciences, and biomedical research.
-
C.
東北大学
東北大学は、日本の宮城県仙台市に本部を置く、研究力と工学・理学分野で特に高い評価を受ける国立総合大学です。
-
D.
National University of Tainan
National University of Tainan is a public research university in Tainan, Taiwan, known for its strengths in education, humanities, and the arts.
-
E.
National Southwestern Associated University
National Southwestern Associated University was a wartime consortium of leading Chinese universities that became renowned for its rigorous academics and for educating many prominent scientists and intellectuals.
- 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: 台北帝国大学 Triple: [帝国大学, includes, 台北帝国大学]
Generated description
台北帝国大学 was a Japanese colonial-era imperial university in Taipei that later became the foundation for National Taiwan University.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 台北帝国大学 Target entity description: 台北帝国大学 was a Japanese colonial-era imperial university in Taipei that later became the foundation for National Taiwan University.
-
A.
國學院大學
國學院大學 is a private Japanese university in Tokyo known for its focus on Shinto studies, Japanese history, and traditional culture.
-
B.
National Yang-Ming University
National Yang-Ming University was a leading Taiwanese research university renowned for its strengths in medicine, life sciences, and biomedical research.
-
C.
東北大学
東北大学は、日本の宮城県仙台市に本部を置く、研究力と工学・理学分野で特に高い評価を受ける国立総合大学です。
-
D.
National University of Tainan
National University of Tainan is a public research university in Tainan, Taiwan, known for its strengths in education, humanities, and the arts.
-
E.
National Southwestern Associated University
National Southwestern Associated University was a wartime consortium of leading Chinese universities that became renowned for its rigorous academics and for educating many prominent scientists and intellectuals.
- 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_69d6aac7953c8190b82caf9d7640fdf9 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e91c045c81908a9024a8aee32f4d |
completed | April 9, 2026, 5:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4ad8c3bec8190987451ab73e79011 |
completed | April 19, 2026, 10:25 a.m. |
| NEDg | Description generation | batch_69e4b12eee348190bee6c84587e4955d |
completed | April 19, 2026, 10:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e4be2bb8c88190a21773b0c43b6b99 |
completed | April 19, 2026, 11:36 a.m. |
Created at: April 8, 2026, 9:31 p.m.