Triple
T5718750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bologna |
E126086
|
entity |
| Predicate | hasNickname |
P39
|
FINISHED |
| Object | La Grassa |
E126087
|
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: La Grassa | Statement: [Bologna, hasNickname, La Grassa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: La Grassa Context triple: [Bologna, hasNickname, 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.
Orotelli
Orotelli is a small town and comune in the province of Nuoro on the island of Sardinia, Italy, known for its traditional Sardinian culture and rural landscape.
-
C.
Bisacquino
Bisacquino is a small town in the Sicilian province of Palermo, Italy, known as the birthplace of film director Frank Capra.
-
D.
Miravalle
Miravalle is a neighborhood located within the Benito Juárez borough of Mexico City, known for its residential character and urban amenities.
-
E.
Bressant
Bressant is a novel by American author Julian Hawthorne, known as one of his early works in 19th-century fiction.
- 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_69c0082e3d548190950169847b43043b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c024e1ec7c8190a08e1b7954db2a9d |
completed | March 22, 2026, 5:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c05a7db0788190b4a5e7b5d9c94588 |
completed | March 22, 2026, 9:09 p.m. |
Created at: March 22, 2026, 3:46 p.m.