Triple
T19529125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Pietro Infine |
E488612
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Cassino |
—
|
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: Cassino | Statement: [San Pietro Infine, locatedNear, Cassino]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cassino Context triple: [San Pietro Infine, locatedNear, Cassino]
-
A.
Cassino
Cassino is a locality within the Italian municipality of Cannobio, situated in the Piedmont region near Lake Maggiore.
-
B.
Cassino
chosen
Cassino is a town in central Italy known for its strategic location and the nearby Monte Cassino, site of a historic Benedictine abbey and major World War II battles.
-
C.
Seregno
Seregno is a town in the Lombardy region of northern Italy, known for its industrial activity and proximity to Milan.
-
D.
Castel di Sangro
Castel di Sangro is a historic town in Italy’s Abruzzo region, known for its scenic Apennine mountain setting and as the subject of the football book "The Miracle of Castel di Sangro."
-
E.
Campogalliano
Campogalliano is a small Italian town and municipality in the Emilia-Romagna region, known for its industrial activity and proximity to the city of Modena.
- 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_69e6363dfd6c8190aaa0b374184965bb |
completed | April 20, 2026, 2:20 p.m. |
Created at: April 10, 2026, 1:41 p.m.