Triple
T17179030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vostochny |
E416932
|
entity |
| Predicate | neuterFormWrittenAs |
P124106
|
FINISHED |
| Object | Восточное |
—
|
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: Восточное | Statement: [Vostochny, neuterFormWrittenAs, Восточное]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: neuterFormWrittenAs Context triple: [Vostochny, neuterFormWrittenAs, Восточное]
-
A.
hasNeuterForm
chosen
Indicates that an entity has a grammatical form specifically used for neuter gender.
-
B.
genderNeutralForm
Indicates that one entity is a gender-neutral linguistic form or expression corresponding to another, more gendered form.
-
C.
nounFormOf
Indicates that one term is the noun form derived from, or corresponding to, another term (typically a verb or adjective).
-
D.
hasFemaleFormOf
Indicates that one entity is the specifically female version or form of another, more general or differently gendered entity.
-
E.
genderedFormOf
Indicates that one term is a gender-specific variant or inflected form corresponding to another, more neutral or differently gendered term.
- 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_69d886d5f34c8190b24564dfaa63f3fb |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3fc0f9a288190b0ddfb673bd8e84b |
completed | April 18, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69e383141ae0819096acd71683637cbc |
completed | April 18, 2026, 1:11 p.m. |
Created at: April 10, 2026, 5:37 a.m.