Triple
T5237928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nice tramway |
E118269
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Nice city centre |
E350536
|
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: Nice city centre | Statement: [Nice tramway, connectsTo, Nice city centre]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nice city centre Context triple: [Nice tramway, connectsTo, Nice city centre]
-
A.
Nice city centre
chosen
Nice city centre is the vibrant commercial and cultural heart of Nice, known for its bustling shopping streets, historic architecture, and proximity to the Mediterranean waterfront.
-
B.
City Centre
City Centre is Mississauga’s primary downtown core, known for its high-density residential towers, major shopping complexes, and civic and cultural facilities.
-
C.
City Centre
City Centre is the central commercial and cultural district of Cambridge, known for its historic university buildings, shops, and public spaces.
-
D.
Nice metropolitan area
The Nice metropolitan area is the urban and economic region centered on the city of Nice on the French Riviera, encompassing its surrounding communes along the Mediterranean coast.
-
E.
Stadtmitte
Stadtmitte is a central Berlin U-Bahn station serving as an important interchange and access point to the city’s historic Mitte district.
- 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_69bd4467db0881909b3b0982df32cc8f |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7b27990c8190b6a3c24de09c8c18 |
completed | March 20, 2026, 4:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bef820285881909f0e569e020a58ae |
completed | March 21, 2026, 7:57 p.m. |
Created at: March 20, 2026, 1:49 p.m.