Triple
T15644674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 監察院 |
E376147
|
entity |
| Predicate | movedToTaiwan |
P10184
|
FINISHED |
| Object | 1949年後隨中華民國政府遷臺 |
—
|
LITERAL 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: 1949年後隨中華民國政府遷臺 | Statement: [監察院, movedToTaiwan, 1949年後隨中華民國政府遷臺]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: movedToTaiwan Context triple: [監察院, movedToTaiwan, 1949年後隨中華民國政府遷臺]
-
A.
yearGovernmentMovedToTaiwan
chosen
Indicates the year in which a government relocated its seat or central administration to Taiwan.
-
B.
movedDomicileFromCountry
Indicates that an entity changed its place of residence from one specified country to another location.
-
C.
immigratedTo
Indicates that an entity moved from its country of origin to live permanently in another specified country or region.
-
D.
intendedToCrossStrait
Indicates that an entity had the purpose or plan to traverse from one side of a strait to the other.
-
E.
movedFor
Indicates that one entity changed its location or position for the benefit, purpose, or in response to another entity.
- F. None of above.
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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ed400ec8190a14a9f7cf3092865 |
completed | April 16, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69deda890140819082608931e993dd61 |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:15 a.m.