Triple
T21964703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ginevra Meloni |
E542427
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Ginevra |
—
|
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: Ginevra | Statement: [Ginevra Meloni, givenName, Ginevra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ginevra Context triple: [Ginevra Meloni, givenName, Ginevra]
-
A.
Ginevra
chosen
Ginevra is a feminine given name, historically linked to the Arthurian figure Guinevere and used in various European languages, notably Italian.
-
B.
Ludovica
Ludovica is an Italian feminine given name, traditionally associated with nobility and derived from the same Germanic roots as names like Louise and Ludwig.
-
C.
Lorenza
Lorenza is a Chilean actress and model best known for her roles in films like "Knock Knock" and "Once Upon a Time in Hollywood."
-
D.
Clarenzo
Clarenzo is a character associated with Izembaro in the world of "Game of Thrones," likely involved in the Braavosi theater troupe.
-
E.
Genaveh
Genaveh is a coastal city and port on the Persian Gulf in Iran’s Bushehr Province.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c47fab1081908dc74a6545dbb051 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f12459e1848190aa8d4ccc97f434b8 |
completed | April 28, 2026, 9:19 p.m. |
Created at: April 16, 2026, 8:01 p.m.