Triple
T9960880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Лев |
E195563
|
entity |
| Predicate | грамматическийРод |
P3087
|
FINISHED |
| Object | мужской |
—
|
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: мужской | Statement: [Лев, грамматическийРод, мужской]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: грамматическийРод Context triple: [Лев, грамматическийРод, мужской]
-
A.
hasGrammaticalGender
chosen
Indicates that one entity assigns or possesses a specific grammatical gender in relation to another entity (such as a word, phrase, or linguistic unit).
-
B.
hasNoGrammaticalGender
Indicates that the referenced entity or term is not associated with any grammatical gender category in the relevant language system.
-
C.
grammaticalForm
Indicates the specific grammatical structure or morphological form that an expression or word takes in a given linguistic context.
-
D.
grammaticalType
Indicates the grammatical category or role (such as part of speech or syntactic function) that an expression has within a language.
-
E.
hasGenderInRussian
Indicates that an entity is associated with a specific grammatical gender in the Russian language.
- 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_69ca82eaaa008190a54fa1a9f954b9ad |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb6d219c48190b2084b0eb07ae125 |
completed | April 2, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69cd1d9ae19c819099fb3635e57c79be |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:47 p.m.