Triple
T17592161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gare de Caen |
E428473
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | city of Caen |
—
|
NE NERFINISHED |
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: city of Caen | Statement: [Gare de Caen, serves, city of Caen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: city of Caen Context triple: [Gare de Caen, serves, city of Caen]
-
A.
City of Caen
chosen
The City of Caen is a historic commune in Normandy, northwestern France, known for its medieval architecture, ties to William the Conqueror, and significant role in World War II.
-
B.
Rouen
Rouen is a historic city in northern France renowned for its medieval architecture, Gothic cathedral, and association with figures like Joan of Arc and the Impressionist painter Claude Monet.
-
C.
Bayeux
Bayeux is a municipality in the Brazilian state of Paraíba, located in the northeastern region of the country and forming part of the João Pessoa metropolitan area.
-
D.
Bayeux
Bayeux is a historic town in Normandy, France, renowned for the medieval Bayeux Tapestry and its proximity to the D-Day landing beaches.
-
E.
Saintes
Saintes is a historic town in southwestern France, known for its well-preserved Roman and medieval heritage, including ancient monuments and religious sites.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889e1030481909950e140c63255b9 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e469e79dac8190953a1ce8fc015b20 |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 5:51 a.m.