Triple
T35794719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francesco Raffaele Nitto |
E1034797
|
entity |
| Predicate | notableAliasLanguage |
P63334
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Francesco Raffaele Nitto, notableAliasLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableAliasLanguage Context triple: [Francesco Raffaele Nitto, notableAliasLanguage, English]
-
A.
alternateLanguageName
chosen
Indicates that an entity has an additional name or label in a different language from its primary or default name.
-
B.
mainLanguageOfAlternativeName
Indicates that a specified language is the primary language in which an alternative name for an entity is expressed.
-
C.
notableMemberLanguage
Indicates that the language is notably associated with or used by a prominent member of the referenced group or entity.
-
D.
notableLanguageOfWorks
Indicates that a particular language is especially prominent or significant among the works created by an entity.
-
E.
notableAuthorInLanguage
Indicates that a person is a particularly prominent or distinguished author who writes in the specified language.
- 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_69f76e1575908190aaa306d843b41c14 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037ce70f54819082946dad8d380825 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a069e6c8190857b611fffb7b867 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:06 p.m.