Triple
T2042912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pont Neuf |
E44783
|
entity |
| Predicate | isNear |
P350
|
FINISHED |
| Object | Place Dauphine |
E221442
|
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: Place Dauphine | Statement: [Pont Neuf, isNear, Place Dauphine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Place Dauphine Context triple: [Pont Neuf, isNear, Place Dauphine]
-
A.
Place Dauphine
chosen
Place Dauphine is a historic, triangular public square in central Paris, known for its quiet charm and classical architecture near the western end of the Île de la Cité.
-
B.
Porte Dauphine
Porte Dauphine is a Paris Métro station on Line 2, located near the Bois de Boulogne in the 16th arrondissement of Paris.
-
C.
Place de Jaude
Place de Jaude is the main central square of Clermont-Ferrand, France, known as a bustling commercial and social hub surrounded by shops, cafes, and historic monuments.
-
D.
Promenade du Paillon
Promenade du Paillon is a central urban park and green corridor in Nice, France, featuring fountains, playgrounds, and landscaped walks stretching between the old town and the city’s main squares.
-
E.
Place d’Italie
Place d’Italie is a major public square and transportation hub in Paris’ 13th arrondissement, known for its busy Métro interchange and surrounding commercial 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_69a889159ec481908f9e4472d9f480c7 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb96f932881908bebfc4176fda7c0 |
completed | March 7, 2026, 5:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae1ffe98248190b6a4428c6c094d35 |
completed | March 9, 2026, 1:18 a.m. |
Created at: March 4, 2026, 7:39 p.m.