Triple
T8656885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yen Chia-kan |
E205441
|
entity |
| Predicate | deathPlace |
P21
|
FINISHED |
| Object | Taipei, Taiwan |
E14412
|
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: Taipei, Taiwan | Statement: [Yen Chia-kan, deathPlace, Taipei, Taiwan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taipei, Taiwan Context triple: [Yen Chia-kan, deathPlace, Taipei, Taiwan]
-
A.
Taipei, Taiwan
chosen
Taipei, Taiwan is the capital and largest city of Taiwan, known as a major political, economic, and cultural center in East Asia.
-
B.
Chiayi City, Taiwan
Chiayi City, Taiwan, is a historic city in southwestern Taiwan known as a gateway to Alishan and for its rich cultural heritage and traditional night markets.
-
C.
Hsinchu, Taiwan
Hsinchu, Taiwan is a major high-tech city often called Taiwan’s “Silicon Valley,” known for its science park and concentration of semiconductor and electronics companies.
-
D.
Tainan
Tainan is a historic city in southern Taiwan known for its well-preserved temples, traditional culture, and status as the island’s former capital.
-
E.
Kaohsiung
Kaohsiung is a major port city in southern Taiwan known for its heavy industry, modern harborfront, and growing cultural and arts scene.
- 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_69ca8350897c819086cde7596fbe5fe7 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc484569788190aa41395854684e6f |
completed | March 31, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ceccec941881908263cd3205f10ccd |
completed | April 2, 2026, 8:09 p.m. |
Created at: March 30, 2026, 6:30 p.m.