Triple
T36767868
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giovanni Battista Betancourt |
E908392
|
entity |
| Predicate | hasItalianizedName |
P17612
|
FINISHED |
| Object | Giovanni Battista Betancourt |
—
|
NE NERFINISHED |
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: Giovanni Battista Betancourt | Statement: [Giovanni Battista Betancourt, hasItalianizedName, Giovanni Battista Betancourt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasItalianizedName Context triple: [Giovanni Battista Betancourt, hasItalianizedName, Giovanni Battista Betancourt]
-
A.
hasAcronymInItalian
Indicates that an entity is associated with an acronym specifically in the Italian language.
-
B.
hasLatinizedName
Indicates that an entity is associated with a version of its name that has been converted into Latin form or spelling.
-
C.
nameInItalian
chosen
Indicates that one entity is the Italian-language name or label used to refer to another entity.
-
D.
hasInternationalName
Indicates that an entity is associated with a name used or recognized in an international or cross-linguistic context.
-
E.
ItalianVersionClaimed
Indicates that an entity asserts or is reported to have an Italian-language version.
- 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_69f76e786ba481909cdcf6cf6b39dd32 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c9f5a8848190ba956ff27f44e396 |
completed | May 3, 2026, 10:19 p.m. |
| PD | Predicate disambiguation | batch_69f7c8999a348190abc1895eaa6e036d |
completed | May 3, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:12 p.m.