Triple
T9397566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quai de Gesvres |
E226383
|
entity |
| Predicate | hasNameInLanguage |
P15
|
FINISHED |
| Object | Quai de Gesvres (fr) |
E226383
|
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 Gesvres (fr) | Statement: [Quai de Gesvres, hasNameInLanguage, Quai de Gesvres (fr)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Quai de Gesvres (fr) Context triple: [Quai de Gesvres, hasNameInLanguage, Quai de Gesvres (fr)]
-
A.
Quai de Gesvres
chosen
Quai de Gesvres is a riverside street along the right bank of the Seine in central Paris, known for its proximity to the historic Île de la Cité and the Hôtel de Ville.
-
B.
Quai de la Gare
Quai de la Gare is a Paris Métro station located in the 13th arrondissement near the Seine, serving the surrounding riverside and cultural areas.
-
C.
Quai de l’Archevêché
Quai de l’Archevêché is a riverside quay on Paris’s Île de la Cité, known for its views of Notre-Dame Cathedral and its location along the Seine.
-
D.
Quai du Général-Guisan
Quai du Général-Guisan is a prominent lakeside promenade and roadway along Lake Geneva in the city of Geneva, Switzerland.
-
E.
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.
- 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_69ca843170f88190800a8ab2b5fc568e |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd51541020819097da2eb60be73760 |
completed | April 1, 2026, 5:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1011aef64819085cbb7e04c2d87b2 |
completed | April 4, 2026, 12:16 p.m. |
Created at: March 30, 2026, 7:46 p.m.