Triple
T4366246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katerina Mikhailovna Maslova |
E98778
|
entity |
| Predicate | associatedWithAuthorThemes |
P49998
|
FINISHED |
| Object | Christian ethics |
—
|
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: Christian ethics | Statement: [Katerina Mikhailovna Maslova, associatedWithAuthorThemes, Christian ethics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithAuthorThemes Context triple: [Katerina Mikhailovna Maslova, associatedWithAuthorThemes, Christian ethics]
-
A.
majorThemeAssociation
chosen
Indicates that one entity is associated with another as a primary or central theme.
-
B.
associatedWithAuthorCycle
Indicates a relationship where an entity is linked to a recurring or cyclical pattern involving an author, such as repeated collaborations, works, or roles over time.
-
C.
placeAssociatedWithAuthor
Indicates a relationship where a place is connected to an author, such as by birth, residence, work, or significant activity.
-
D.
hasAuthorRelationship
Indicates a relationship where one entity serves as the author or creator of another entity (such as a work, document, or resource).
-
E.
hasAuthorRelationshipToSubject
Indicates that an entity serves as the author or creator of the specified subject.
- 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_69b3454c772081908e20173e379e8ebe |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35200263081909bb326a4d7a8db99 |
completed | March 12, 2026, 11:53 p.m. |
| PD | Predicate disambiguation | batch_69b34f53e3cc8190bf5d4dbe2413bf65 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:17 p.m.