Triple
T21882029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montani Semper Liberi |
E540309
|
entity |
| Predicate | hasGrammaticalPerson |
P29570
|
FINISHED |
| Object | third person |
—
|
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: third person | Statement: [Montani Semper Liberi, hasGrammaticalPerson, third person]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGrammaticalPerson Context triple: [Montani Semper Liberi, hasGrammaticalPerson, third person]
-
A.
grammaticalPerson
chosen
Indicates the grammatical role of a participant in speech (such as first, second, or third person) in relation to the speaker and listener.
-
B.
grammaticalPersonOfVerb
Indicates the grammatical person (first, second, or third person) associated with a given verb form.
-
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.
hasGrammaticalNumber
Indicates that an expression is associated with a specific grammatical number category (such as singular, plural, or dual) in a language.
-
E.
hasSubjectPronouns
Indicates that an entity is associated with one or more pronouns that function as its grammatical subject in sentences.
- 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_69e0c479a98081908ce333853fdd4348 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f118e890088190aa3023c78a99a536 |
completed | April 28, 2026, 8:30 p.m. |
| PD | Predicate disambiguation | batch_69e6be9394f88190945ddd1dc004d29d |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 7:04 p.m.