Triple
T19510787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terra Nostra |
E488144
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Ludovico |
—
|
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: Ludovico | Statement: [Terra Nostra, hasCharacter, Ludovico]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ludovico Context triple: [Terra Nostra, hasCharacter, Ludovico]
-
A.
Ludovico
chosen
Ludovico is an Italian given name, historically borne by various notable figures in art, music, and nobility.
-
B.
Ottavio
Ottavio is an Italian given name historically borne by notable figures such as Renaissance nobles and churchmen, including members of the Farnese family.
-
C.
Ferdinando
Ferdinando is a masculine given name of Italian and Spanish origin, related to the name Ferdinand and historically borne by various European nobles and notable figures.
-
D.
Francesco
Francesco is the Italian given name of Frank Nitti, a notorious American mobster and key figure in Al Capone’s Chicago Outfit.
-
E.
Francesco
Francesco is the given name of Italian actor Franco Nero, renowned for his iconic role in the Spaghetti Western film "Django."
- 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_69d8e8da8bec819081f400199491ccc3 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63516572c8190a8719c51fd3f7147 |
completed | April 20, 2026, 2:15 p.m. |
Created at: April 10, 2026, 1:40 p.m.