Triple
T9101341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pelageya Nilovna Vlasova |
E218162
|
entity |
| Predicate | relationshipToPavelVlasov |
P87154
|
FINISHED |
| Object | mother |
—
|
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: mother | Statement: [Pelageya Nilovna Vlasova, relationshipToPavelVlasov, mother]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToPavelVlasov Context triple: [Pelageya Nilovna Vlasova, relationshipToPavelVlasov, mother]
-
A.
relationshipToPierreBezukhov
Indicates the specific type of personal or social relationship an entity has to Pierre Bezukhov.
-
B.
relationshipToMoscow
Indicates the type or nature of a connection, association, or relevance that something has specifically to Moscow.
-
C.
relationshipWithMarinaMniszech
Indicates that an entity has a personal, political, or social relationship with Marina Mniszech.
-
D.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
-
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_69ca83d9844081908e561e367fda6d45 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc971435d08190b5007ed44ac0a364 |
completed | April 1, 2026, 3:55 a.m. |
| PD | Predicate disambiguation | batch_69cc65fc7f408190a5846e29ab3b97e5 |
completed | April 1, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69cc6a3c78388190a7436acc0e44ff55 |
completed | April 1, 2026, 12:43 a.m. |
Created at: March 30, 2026, 7:15 p.m.