Triple
T7283254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Susa |
E163800
|
entity |
| Predicate | hasDemonym |
P191
|
FINISHED |
| Object | Segusini |
E235215
|
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: Segusini | Statement: [Susa, hasDemonym, Segusini]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Segusini Context triple: [Susa, hasDemonym, Segusini]
-
A.
Segusio
chosen
Segusio was an ancient Roman town in the Alps, strategically located on key transalpine routes in what is now Susa, Italy.
-
B.
Leonessa
Leonessa is a historic mountain town in central Italy, known for its medieval architecture and scenic location in the Apennines.
-
C.
Galla
Galla was a Roman empress of the late 4th century, daughter of Emperor Valentinian I and wife of Emperor Theodosius I.
-
D.
Garessio
Garessio is a historic town in the Piedmont region of northwestern Italy, situated in a mountainous area near the Ligurian border.
-
E.
Agaete
Agaete is a coastal town on the northwest of Gran Canaria in Spain’s Canary Islands, known for its rugged cliffs, natural pools, and traditional fishing harbor.
- 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_69c6886093b88190a254b1ce6db8bae7 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb4ec2088190a6713eaa221d49a6 |
completed | March 27, 2026, 8:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7db3ae6a08190820c7096cbfea521 |
completed | March 28, 2026, 1:44 p.m. |
Created at: March 27, 2026, 2:59 p.m.