Triple
T9400550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carentan station |
E226455
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Caen station |
E428473
|
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: Caen station | Statement: [Carentan station, connectsTo, Caen station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caen station Context triple: [Carentan station, connectsTo, Caen station]
-
A.
Gare de Caen
chosen
Gare de Caen is the main railway station serving the city of Caen in northwestern France, providing regional and long-distance train connections.
-
B.
Reims station
Reims station is the main railway station serving the city of Reims in northeastern France, providing regional and high-speed train connections.
-
C.
Pontoise station
Pontoise station is a major railway and RER hub in the northwestern suburbs of Paris, serving as an important terminus and interchange point for regional and suburban trains.
-
D.
Gare du Havre
Gare du Havre is the main railway station in Le Havre, France, serving as a key regional and intercity transport hub.
-
E.
Calais-Fréthun railway station
Calais-Fréthun railway station is an international rail hub in northern France that connects Calais to high-speed domestic and cross-Channel services, including Eurostar trains.
- 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_69d1012753088190bc73b7c577109e76 |
completed | April 4, 2026, 12:16 p.m. |
Created at: March 30, 2026, 7:46 p.m.