Triple
T8101632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Susan Patterson |
E189126
|
entity |
| Predicate | hasCollaborativeRoleWithSpouse |
P80466
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Susan Patterson, hasCollaborativeRoleWithSpouse, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCollaborativeRoleWithSpouse Context triple: [Susan Patterson, hasCollaborativeRoleWithSpouse, yes]
-
A.
spouseMemberOf
Indicates that a person’s spouse is a member of a specified group, organization, or entity.
-
B.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
-
C.
hasAuthorSpouse
Indicates that the spouse of the subject entity is the author of the related work or entity.
-
D.
spouseCollective
Indicates that a group of individuals collectively stand in a spousal or marriage-like relationship to another group or entity.
-
E.
spouseInstanceOf
Indicates that one entity is the specific spouse (marriage partner) instance of another entity.
- F. None of above. chosen
Provenance (4 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_69ca82b886d88190a9cba0d5a4a27521 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb42bbf20c8190aa8c272b5c39002d |
completed | March 31, 2026, 3:42 a.m. |
| PD | Predicate disambiguation | batch_69cb04a14cd88190a79ed26cbeec1c33 |
completed | March 30, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69cb14be17208190bb51c3dfcb613f20 |
completed | March 31, 2026, 12:26 a.m. |
Created at: March 30, 2026, 5:31 p.m.