Triple
T20949110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shcherbatskaya |
E515931
|
entity |
| Predicate | familyStatusInWork |
P103226
|
FINISHED |
| Object | Russian nobility |
—
|
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: Russian nobility | Statement: [Shcherbatskaya, familyStatusInWork, Russian nobility]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: familyStatusInWork Context triple: [Shcherbatskaya, familyStatusInWork, Russian nobility]
-
A.
familySocialStatus
chosen
Indicates the social standing or class position associated with a person’s family within a society.
-
B.
hasFamilySituation
Indicates the familial status or circumstances that apply to an entity, such as their family composition, responsibilities, or living situation.
-
C.
spouseInWork
Indicates that two entities are spouses within the context of a particular work (such as a book, film, or series), rather than in real life.
-
D.
householdStatus
Indicates the type or condition of a person’s living arrangement within a household, such as their role, membership, or current residency status.
-
E.
hasFamilyRelationInWork
Indicates that there exists a family relationship between two entities within the context of a specific work (e.g., book, film, or other creative work).
- 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_69e0b4fcd678819087a304291f14330a |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fadc08148190b4ff710f94462a26 |
completed | April 21, 2026, 4:19 a.m. |
| PD | Predicate disambiguation | batch_69e5c9b1bae48190a845165fed1b005e |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 1:15 p.m.