Triple
T12951117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erma Ora James |
E309893
|
entity |
| Predicate | spousePositionRepresented |
P4763
|
FINISHED |
| Object | United States Senator from West Virginia |
—
|
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: United States Senator from West Virginia | Statement: [Erma Ora James, spousePositionRepresented, United States Senator from West Virginia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spousePositionRepresented Context triple: [Erma Ora James, spousePositionRepresented, United States Senator from West Virginia]
-
A.
spouse represented
Indicates that one person legally or formally acted on behalf of their spouse, such as in a professional, legal, or official capacity.
-
B.
spouseOffice
Indicates that one entity holds an office or position that is associated with, or held by, the spouse of another entity.
-
C.
positionHeldBySpouse
chosen
Indicates that a particular position, role, or office is or was held by the spouse of a given person.
-
D.
spouseAppointedBy
Indicates that a person’s spouse was selected or assigned to a role or position by the referenced appointing entity.
-
E.
hasSpouseOrPartnerInLegalCaseWith
Indicates that two individuals are spouses or partners who are jointly involved in the same legal case.
- 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_69d7bdfb57a88190836b743e2825feca |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97dba57988190b786ffed55687a72 |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 5:43 p.m.