Triple
T34181749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruth Condomine |
E876838
|
entity |
| Predicate | isWifeNumber |
P178488
|
FINISHED |
| Object | second wife of Charles Condomine |
—
|
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: second wife of Charles Condomine | Statement: [Ruth Condomine, isWifeNumber, second wife of Charles Condomine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isWifeNumber Context triple: [Ruth Condomine, isWifeNumber, second wife of Charles Condomine]
-
A.
coWifeOf
Indicates that two women are married to the same spouse at the same time, making them co-wives in a polygamous marriage.
-
B.
spouseInstanceOf
Indicates that one entity is the specific spouse (marriage partner) instance of another entity.
-
C.
coSpouse
Indicates that two individuals are married to each other as spouses.
-
D.
hasSpouseUsingFeminineForm
Indicates that one entity has a spouse, and this spousal relationship is expressed or recorded using a feminine grammatical form.
-
E.
intendedSpouse
Indicates that one person is planned or expected to become the spouse of another, typically through an intended or future marriage.
- 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_69f349ae640c8190b9cd220b5368d8b6 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f710aaff588190adc6cc5b7d5424cc |
completed | May 3, 2026, 9:08 a.m. |
| PD | Predicate disambiguation | batch_69f70f3c5bfc81908585f52e196dafe5 |
completed | May 3, 2026, 9:02 a.m. |
| PDg | Predicate description generation | batch_69f70fddd43c819088dee5a448c72cbe |
completed | May 3, 2026, 9:05 a.m. |
Created at: May 1, 2026, 1:54 a.m.