Triple
T5244026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meliora |
E118413
|
entity |
| Predicate | grammaticalCase |
P7764
|
FINISHED |
| Object | neuter plural |
—
|
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: neuter plural | Statement: [Meliora, grammaticalCase, neuter plural]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grammaticalCase Context triple: [Meliora, grammaticalCase, neuter plural]
-
A.
numberOfGrammaticalCases
Indicates the relationship that specifies how many distinct grammatical cases a language or linguistic system possesses.
-
B.
grammaticalForm
chosen
Indicates the specific grammatical structure or morphological form that an expression or word takes in a given linguistic context.
-
C.
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).
-
D.
grammaticalPerson
Indicates the grammatical role of a participant in speech (such as first, second, or third person) in relation to the speaker and listener.
-
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_69bd4468aacc8190a8196f71855cdf4f |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7b4da7308190856cdcee9cca41eb |
completed | March 20, 2026, 4:52 p.m. |
| PD | Predicate disambiguation | batch_69bd77c1397c8190a7fd844d7a396e54 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:49 p.m.