Triple
T35836630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 吳彥祖 |
E1035956
|
entity |
| Predicate | 婚姻狀況 |
P20884
|
FINISHED |
| Object | 已婚 |
—
|
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: 已婚 | Statement: [吳彥祖, 婚姻狀況, 已婚]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 婚姻狀況 Context triple: [吳彥祖, 婚姻狀況, 已婚]
-
A.
marital status
chosen
Indicates the legal or social state of a person’s marriage-related relationship, such as being single, married, divorced, or widowed.
-
B.
spouseStatus
Indicates the marital relationship status between two individuals, such as whether they are currently spouses, formerly spouses, or not married to each other.
-
C.
hasCivilStatus
Indicates the civil or marital status that applies to a person or entity (e.g., single, married, divorced).
-
D.
civilStatus
Indicates the legal marital or family-related status of a person (e.g., single, married, divorced, widowed) at a given time.
-
E.
marriageLegalStatus
Indicates the legal status of a marriage relationship between entities, such as whether it is valid, invalid, pending, or dissolved under applicable law.
- 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_69f76e192a94819082db360cb91e6a8d |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7aa699d68819081ed363931894ab3 |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8d219f8819081dc4ce3c83ca0cb |
completed | May 3, 2026, 7:58 p.m. |
Created at: May 3, 2026, 4:06 p.m.