Triple
T34403282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goryachev |
E883038
|
entity |
| Predicate | hasFeminineOrthographicFormInRussian |
P52140
|
FINISHED |
| Object | Горячева |
—
|
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: Горячева | Statement: [Goryachev, hasFeminineOrthographicFormInRussian, Горячева]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFeminineOrthographicFormInRussian Context triple: [Goryachev, hasFeminineOrthographicFormInRussian, Горячева]
-
A.
hasFeminineFormInSomeLanguages
chosen
Indicates that the referenced entity has a distinct feminine grammatical or lexical form in at least one language.
-
B.
hasFeminineFormInCzechAndSlovak
Indicates that an entity has a specifically feminine grammatical or lexical form in the Czech and Slovak languages.
-
C.
hasFemaleFormOf
Indicates that one entity is the specifically female version or form of another, more general or differently gendered entity.
-
D.
hasMasculineForm
Indicates that an entity has a corresponding masculine grammatical or lexical form.
-
E.
hasNeuterForm
Indicates that an entity has a grammatical form specifically used for neuter gender.
- 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_69f349c1f2208190a09a489bb8b2719d |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f9fd6834cc8190aa27153d6a99f3bb |
completed | May 5, 2026, 2:23 p.m. |
| PD | Predicate disambiguation | batch_69f7cf769338819092a5f42653dcc956 |
completed | May 3, 2026, 10:43 p.m. |
Created at: May 1, 2026, 1:59 a.m.