Triple
T21880287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Fat One |
E540259
|
entity |
| Predicate | translationOf |
P2303
|
FINISHED |
| Object | La Grassa |
—
|
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: La Grassa | Statement: [The Fat One, translationOf, La Grassa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: La Grassa Context triple: [The Fat One, translationOf, La Grassa]
-
A.
La Grassa
chosen
La Grassa is a famous nickname for the Italian city of Bologna, highlighting its rich culinary tradition and renowned food culture.
-
B.
LaPasse
LaPasse is a small rural community in eastern Ontario, Canada, situated along the Ottawa River within the township of Whitewater Region.
-
C.
Labriola
Labriola is an Italian surname borne by several notable figures, including philosophers, politicians, and writers.
-
D.
Molinara
Molinara is a light-colored Italian red wine grape variety traditionally used in blends from the Veneto region, particularly in wines like Bardolino and Valpolicella.
-
E.
Seravezza
Seravezza is a historic Tuscan town in central Italy, known for its marble quarries and scenic location in the Apuan Alps.
- 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_69e0c479a98081908ce333853fdd4348 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f118e600c08190bc96203f03f1e58a |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 16, 2026, 7:04 p.m.