Triple
T17589927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 朱立倫 |
E428417
|
entity |
| Predicate | mayorOf |
P185
|
FINISHED |
| Object | 新北市 |
—
|
NE NERFINISHED |
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: 新北市 | Statement: [朱立倫, mayorOf, 新北市]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 新北市 Context triple: [朱立倫, mayorOf, 新北市]
-
A.
新竹市
新竹市 is a city in northern Taiwan known for its high-tech industry hub, particularly the Hsinchu Science Park, and its strong education and research institutions.
-
B.
臺北市
臺北市是臺灣的首都與最大都會區之一，為國家的政治、經濟、文化與交通中心。
-
C.
New Taipei City
chosen
New Taipei City is a populous special municipality in northern Taiwan that encircles Taipei and serves as a major residential, industrial, and transportation hub of the Taipei metropolitan area.
-
D.
基隆
基隆是位於臺灣北部的港口城市，以多雨氣候和重要海運樞紐地位聞名。
-
E.
Xinyi District
Xinyi District is a modern commercial and financial hub of Taipei, Taiwan, known for its skyscrapers, luxury shopping, and vibrant nightlife.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889e1030481909950e140c63255b9 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e469e62d5c81909134e30a6d0f2e20 |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 5:51 a.m.