Triple
T9400551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carentan station |
E226455
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Cherbourg station |
E758954
|
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: Cherbourg station | Statement: [Carentan station, connectsTo, Cherbourg station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cherbourg station Context triple: [Carentan station, connectsTo, Cherbourg station]
-
A.
Gare de Cherbourg
chosen
Gare de Cherbourg is a major railway station in Cherbourg-en-Cotentin, France, serving as a key regional and intercity rail terminus in Normandy.
-
B.
Gare du Havre
Gare du Havre is the main railway station in Le Havre, France, serving as a key regional and intercity transport hub.
-
C.
Gare de Caen
Gare de Caen is the main railway station serving the city of Caen in northwestern France, providing regional and long-distance train connections.
-
D.
Havre station
Havre station is a historic Amtrak passenger rail station in Havre, Montana, serving as a key stop along the Empire Builder route across the northern United States.
-
E.
Rennes railway station
Rennes railway station is the main rail hub of the city of Rennes in western France, serving high-speed TGV, regional, and local train services.
- 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_69cd5156b9588190bafb6b1c3ee3c0ed |
completed | April 1, 2026, 5:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1079798048190a1bd5318df4b1649 |
completed | April 4, 2026, 12:44 p.m. |
Created at: March 30, 2026, 7:46 p.m.