Triple
T9353204
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quai aux Fleurs |
E225067
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Quai de la Corse |
E251186
|
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: Quai de la Corse | Statement: [Quai aux Fleurs, connectsTo, Quai de la Corse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Quai de la Corse Context triple: [Quai aux Fleurs, connectsTo, Quai de la Corse]
-
A.
Quai de la Corse
chosen
Quai de la Corse is a riverside quay on Paris’s Île de la Cité, lining the Seine near landmarks such as the flower market and Notre-Dame Cathedral.
-
B.
Quai de Bourbon
Quai de Bourbon is a historic riverside quay on the Île Saint-Louis in central Paris, known for its elegant 17th-century townhouses and views over the Seine.
-
C.
Quai de la Douane
Quai de la Douane is a waterfront quay in the Port of Nice, France, serving as a docking and loading area for maritime traffic.
-
D.
Quai de la Rapée
Quai de la Rapée is a Paris Métro station located near the Seine in the 12th arrondissement, serving as a stop on the city’s rapid transit network.
-
E.
Quai de Conti
Quai de Conti is a historic riverside quay on the Left Bank of the Seine in central Paris, known for its cultural institutions and picturesque views.
- 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_69ca842abfd48190949d71c3b86eeba8 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4f9515008190b01fbb43d673de2a |
completed | April 1, 2026, 5:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1c3f6f54c8190b0320d9cb1ae356c |
completed | April 5, 2026, 2:07 a.m. |
Created at: March 30, 2026, 7:41 p.m.