Triple
T579664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Estonian language |
E15029
|
entity |
| Predicate | numberOfGrammaticalCases |
P15726
|
FINISHED |
| Object | 14 |
—
|
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: 14 | Statement: [Estonian language, numberOfGrammaticalCases, 14]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfGrammaticalCases Context triple: [Estonian language, numberOfGrammaticalCases, 14]
-
A.
hasCaseForms
Indicates that an entity possesses multiple grammatical case variants or inflected forms associated with it.
-
B.
hasGrammaticalNumber
Indicates that an expression is associated with a specific grammatical number category (such as singular, plural, or dual) in a language.
-
C.
grammaticalForm
Indicates the specific grammatical structure or morphological form that an expression or word takes in a given linguistic context.
-
D.
hasNounClassSystem
Indicates that an entity possesses a grammatical system in which nouns are categorized into distinct classes that affect their agreement with other elements in the language.
-
E.
hasGrammaticalGender
Indicates that one entity assigns or possesses a specific grammatical gender in relation to another entity (such as a word, phrase, or linguistic unit).
- 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_69a4935783b8819082b77726ec10cc42 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49b6c358081908f458b9e3e208c0d |
completed | March 1, 2026, 8:02 p.m. |
| PD | Predicate disambiguation | batch_69a494c692288190b88f30299516b5ba |
completed | March 1, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69a4985a2d08819090947895d9439e06 |
completed | March 1, 2026, 7:49 p.m. |
Created at: March 1, 2026, 7:33 p.m.