Triple
T9960893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Лев |
E195563
|
entity |
| Predicate | семантическоеПоле |
P91671
|
FINISHED |
| Object | животные |
—
|
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: животные | Statement: [Лев, семантическоеПоле, животные]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: семантическоеПоле Context triple: [Лев, семантическоеПоле, животные]
-
A.
semanticRootMeaning
Indicates the fundamental or core meaning that underlies a word, phrase, or expression in a semantic structure.
-
B.
linguisticField
Indicates that something pertains to or is associated with a particular area or subdiscipline within linguistics.
-
C.
semanticsDetail
Indicates a more specific or fine-grained semantic characterization or nuance of a broader meaning or interpretation.
-
D.
partOfLexicon
Indicates that a linguistic unit (such as a word or expression) belongs to or is included within a particular lexicon or vocabulary set.
-
E.
conceptualMeaning
Indicates the abstract idea, concept, or underlying significance that something represents or conveys.
- 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_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. |
| PDg | Predicate description generation | batch_69cd36f112bc81908b473787e702de2f |
completed | April 1, 2026, 3:17 p.m. |
Created at: March 30, 2026, 8:47 p.m.