Triple
T7968633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Law Kar-ying |
E185267
|
entity |
| Predicate | hasSpouseSince |
P67588
|
FINISHED |
| Object | Liza Wang, married 2009 |
—
|
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: Liza Wang, married 2009 | Statement: [Law Kar-ying, hasSpouseSince, Liza Wang, married 2009]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpouseSince Context triple: [Law Kar-ying, hasSpouseSince, Liza Wang, married 2009]
-
A.
spouseOfSince
chosen
Indicates that two individuals are spouses and specifies the date or time from which their marital relationship has been in effect.
-
B.
metSpouseAt
Indicates that one person first encountered or became acquainted with their spouse at a particular place, event, or time.
-
C.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
-
D.
marriedBy
Indicates that one entity is the officiant or authority who performs and formalizes the marriage of another entity.
-
E.
marriedIn
Indicates that two entities entered into a marital relationship at a specific place or within a particular jurisdiction.
- 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_69ca8297699481909b75a405f01e03af |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3bd06ee081908c5080003fb7b8f7 |
completed | March 31, 2026, 3:13 a.m. |
| PD | Predicate disambiguation | batch_69cb047a8e4c81909b79e0f0bf56440c |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:13 p.m.