Triple
T19103851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mademoiselle Bourienne |
E467601
|
entity |
| Predicate | relationshipToPrinceNikolaiBolkonsky |
P134388
|
FINISHED |
| Object | dependent |
—
|
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: dependent | Statement: [Mademoiselle Bourienne, relationshipToPrinceNikolaiBolkonsky, dependent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToPrinceNikolaiBolkonsky Context triple: [Mademoiselle Bourienne, relationshipToPrinceNikolaiBolkonsky, dependent]
-
A.
relationshipToPierreBezukhov
Indicates the specific type of personal or social relationship an entity has to Pierre Bezukhov.
-
B.
relationshipToOnegin
Indicates the specific interpersonal or familial relationship that one entity has to the person named Onegin.
-
C.
relationshipToPavelVlasov
Indicates the nature or type of relationship an entity has with Pavel Vlasov.
-
D.
relationshipToPrinceDauntless
Indicates the specific familial, social, or interpersonal connection an entity has with Prince Dauntless.
-
E.
PierreBezukhovPortrayedBy
Indicates that a particular actor portrays the character Pierre Bezukhov in a performance or adaptation.
- 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_69d8dd05ac4c8190b1967d8f97f3fb2f |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e36f84048190a62c52411eb55411 |
completed | April 20, 2026, 8:27 a.m. |
| PD | Predicate disambiguation | batch_69e4b9ac41848190afd0f33b42cebe99 |
completed | April 19, 2026, 11:17 a.m. |
| PDg | Predicate description generation | batch_69e4bfe8a06081909fd5c28a33e9f218 |
completed | April 19, 2026, 11:43 a.m. |
Created at: April 10, 2026, 12:04 p.m.