Triple
T2946777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barbara Müller |
E79520
|
entity |
| Predicate | supportedSpouseWork |
P10642
|
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: [Barbara Müller, supportedSpouseWork, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportedSpouseWork Context triple: [Barbara Müller, supportedSpouseWork, yes]
-
A.
spouseOccupation
Indicates that one person’s spouse has a particular job, profession, or occupation.
-
B.
spouse
Indicates that two entities are married to each other in a legally or socially recognized partnership.
-
C.
spouseStatus
Indicates the marital relationship status between two individuals, such as whether they are currently spouses, formerly spouses, or not married to each other.
-
D.
supportedByWork
chosen
Indicates that one entity’s existence, validity, or outcome is backed, justified, or enabled by the work or efforts of another entity.
-
E.
spouseType
Indicates the specific role or category of a person within a spousal relationship (e.g., husband, wife, partner).
- 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_69ad8b1089588190b74d9e2505e45762 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad98b3f86c819094526c2af611bfb5 |
completed | March 8, 2026, 3:41 p.m. |
| PD | Predicate disambiguation | batch_69ad960a70ac8190816b5ae3e8631031 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:56 p.m.