Triple
T15292284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Superga hill |
E365555
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Chieri |
E502347
|
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: Chieri | Statement: [Superga hill, nearbyCity, Chieri]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chieri Context triple: [Superga hill, nearbyCity, Chieri]
-
A.
Chieri
chosen
Chieri is a historic town and comune in the Piedmont region of northwestern Italy, known for its medieval architecture and proximity to the city of Turin.
-
B.
Piossasco
Piossasco is a municipality in the Metropolitan City of Turin in the Piedmont region of northwestern Italy.
-
C.
Aosta
Aosta is a historic town in northwestern Italy known as the capital of the Aosta Valley region and for its well-preserved Roman and medieval architecture.
-
D.
Carassai
Carassai is a small historic hill town in Italy’s Marche region, known for its medieval architecture and scenic countryside setting.
-
E.
Ivrea
Ivrea is a historic town in Italy’s Piedmont region, known for its medieval architecture, industrial heritage, and the famous Battle of the Oranges carnival.
- 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_69d85a103d9081908c1ea6c4c73ac8e3 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03680b60c8190a3ea54a9d34c8105 |
completed | April 16, 2026, 1:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff133d171c8190918c9624bcdb7451 |
completed | May 9, 2026, 10:58 a.m. |
Created at: April 10, 2026, 3:15 a.m.