Triple
T21681939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ivan Fyodorovich Shponka and His Aunt |
E535128
|
entity |
| Predicate | auntCharacterRole |
P145429
|
FINISHED |
| Object | domineering relative |
—
|
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: domineering relative | Statement: [Ivan Fyodorovich Shponka and His Aunt, auntCharacterRole, domineering relative]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: auntCharacterRole Context triple: [Ivan Fyodorovich Shponka and His Aunt, auntCharacterRole, domineering relative]
-
A.
auntOccupation
Indicates that an individual’s aunt holds or performs a particular occupation or job.
-
B.
auntOf
Indicates that one person is the aunt of another, typically as the sibling (or sibling-in-law) of a parent or sometimes an older female relative in an extended family role.
-
C.
auntAndFosterMother
Indicates that one person is both the aunt of another person and also serves as that person’s foster mother.
-
D.
hasAunt
Indicates that one entity is the aunt of another, typically meaning a sister (or sister-in-law) of a parent of that entity.
-
E.
relationshipToAuntEller
Indicates the specific familial relationship that an entity has to Aunt Eller (e.g., whether and how they are related to her).
- 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_69e0c469b6ec8190aee4cadd1527db91 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef96c69990819088a1134ecea09099 |
completed | April 27, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69e6968abfdc81909cf9e0bd72db9eca |
completed | April 20, 2026, 9:11 p.m. |
| PDg | Predicate description generation | batch_69e69cb4bcbc8190a4fc2d508df107be |
completed | April 20, 2026, 9:37 p.m. |
Created at: April 16, 2026, 6:43 p.m.