Triple
T579735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hungarian language |
E15030
|
entity |
| Predicate | hasNumberOfCases |
P1437
|
FINISHED |
| Object | more than 15 grammatical cases |
—
|
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: more than 15 grammatical cases | Statement: [Hungarian language, hasNumberOfCases, more than 15 grammatical cases]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfCases Context triple: [Hungarian language, hasNumberOfCases, more than 15 grammatical cases]
-
A.
hasNumberOfCasesApprox
chosen
Indicates that an entity is associated with an approximate (not exact) count of cases.
-
B.
numberOfCases
Indicates the total count of individual instances, occurrences, or records associated with a particular situation, condition, or category.
-
C.
hasCase
Indicates that one entity is involved in, associated with, or characterized by a particular case, instance, or occurrence represented by another entity.
-
D.
hasTypeOfCase
Indicates that an entity is associated with or classified under a particular type or category of case.
-
E.
hasCaseForms
Indicates that an entity possesses multiple grammatical case variants or inflected forms associated with it.
- 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_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. |
Created at: March 1, 2026, 7:33 p.m.