Triple
T33484397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valeria |
E857569
|
entity |
| Predicate | hasDiminutiveInRussian |
P456
|
FINISHED |
| Object | Lera |
—
|
NE NERFINISHED |
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: Lera | Statement: [Valeria, hasDiminutiveInRussian, Lera]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDiminutiveInRussian Context triple: [Valeria, hasDiminutiveInRussian, Lera]
-
A.
hasDiminutive
chosen
Indicates that one entity is a diminutive form or smaller/affectionate variant of another entity.
-
B.
nameInRussian
Indicates that an entity is known or referred to by a specific name when expressed in the Russian language.
-
C.
hasNameInRusyn
Indicates that an entity has a specific name or label expressed in the Rusyn language.
-
D.
hasPatronymicDerivative
Indicates that one name or term is derived from another by forming a patronymic, typically expressing descent or lineage from a person.
-
E.
hasAffectionateNicknameFor
Indicates that one entity uses or assigns a fond, affectionate, or endearing nickname to another entity.
- 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_69f3497547608190a1a0f2365fb713ee |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fed83b1d188190a318b0ad3003200a |
completed | May 9, 2026, 6:46 a.m. |
| PD | Predicate disambiguation | batch_69fed78e03548190b6e6ad93ae8d131d |
completed | May 9, 2026, 6:43 a.m. |
Created at: May 1, 2026, 1:38 a.m.