Triple
T4321478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maser |
E96525
|
entity |
| Predicate | hasLocalLanguage |
P4185
|
FINISHED |
| Object | Venetian |
E127641
|
NE 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: Venetian | Statement: [Maser, hasLocalLanguage, Venetian]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Venetian Context triple: [Maser, hasLocalLanguage, Venetian]
-
A.
Venetian language
chosen
The Venetian language is a Romance language spoken primarily in the Veneto region of Italy, historically important in trade and culture across the Adriatic and Mediterranean.
-
B.
Genoese Italian
Genoese Italian is a regional variety of the Italian language spoken in and around the city of Genoa in Liguria, known for its distinct phonology and vocabulary.
-
C.
Milanese
Milanese is a Western Lombard dialect spoken primarily in and around the city of Milan in northern Italy.
-
D.
Triestine Venetian dialect
The Triestine Venetian dialect is a regional variety of the Venetian language spoken in and around Trieste, characterized by a blend of Venetian, Slovene, German, and local linguistic influences.
-
E.
Florinese
Florinese refers to a fictional nationality from the kingdom of Florin in William Goldman’s novel and the film adaptation "The Princess Bride."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69b345422aac81909ddbadae437d122e |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3511608dc8190afe912aa605ecace |
completed | March 12, 2026, 11:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5d08d70408190aca5793a480cf54f |
completed | March 14, 2026, 9:18 p.m. |
Created at: March 12, 2026, 11:12 p.m.