Triple
T25588318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chiang Fang-liang |
E641447
|
entity |
| Predicate | marriedToPoliticalLeader |
P116912
|
FINISHED |
| Object | Chiang Ching-kuo |
—
|
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: Chiang Ching-kuo | Statement: [Chiang Fang-liang, marriedToPoliticalLeader, Chiang Ching-kuo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriedToPoliticalLeader Context triple: [Chiang Fang-liang, marriedToPoliticalLeader, Chiang Ching-kuo]
-
A.
marriedToPolitician
chosen
Indicates that a person is married to someone who holds or has held a political office or role.
-
B.
marriedToHeadOfGovernmentOf
Indicates that one entity is the spouse of the person who holds the position of head of government of the other entity.
-
C.
spouseOfLeader
Indicates that one entity is the married partner (spouse) of another entity who holds a leadership position.
-
D.
marriedToDuringOffice
Indicates that one person was married to another person specifically during the time they held a particular office or position.
-
E.
spouseOfHeadOfState
Indicates that one person is the spouse (married partner) of a head of state.
- 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_69e75dc42b588190a98b58e0df359674 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f621fcea1481909b6f8b3af1ee6820 |
completed | May 2, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69f620dc38088190b56b2b15ed75b3c2 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 21, 2026, 4:18 p.m.