Triple
T7283225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Susa |
E163800
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Turin |
E15144
|
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: Turin | Statement: [Susa, locatedNear, Turin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Turin Context triple: [Susa, locatedNear, Turin]
-
A.
Turin
chosen
Turin is a major city in northern Italy known for its rich history, Baroque architecture, automotive industry, and role as a cultural and economic hub.
-
B.
Turin
Turin is a small town located in Coweta County in the U.S. state of Georgia.
-
C.
Metropolitan City of Turin
The Metropolitan City of Turin is an Italian administrative region in Piedmont that encompasses the city of Turin and its surrounding municipalities, coordinating local governance, infrastructure, and regional development.
-
D.
Milano
Milano is a popular line of chocolate-filled sandwich cookies produced by Pepperidge Farm, a subsidiary of Campbell Soup Company.
-
E.
Cuneo
Cuneo is a city in the Piedmont region of northwestern Italy, known for its Alpine setting, agricultural traditions, and use of the Piedmontese language.
- 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_69c7db3450208190b67e4329a531ad0c |
completed | March 28, 2026, 1:44 p.m. |
Created at: March 27, 2026, 2:59 p.m.