Triple
T702697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Channel |
E14031
|
entity |
| Predicate | hasMajorPort |
P942
|
FINISHED |
| Object | Calais |
E30799
|
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: Calais | Statement: [Channel, hasMajorPort, Calais]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Calais Context triple: [Channel, hasMajorPort, Calais]
-
A.
Calais
chosen
Calais is a major French port city on the northern coast, serving as one of the primary crossing points between France and England.
-
B.
Cherbourg
Cherbourg is a major French port city on the Cotentin Peninsula, known for its strategic naval harbor and cross-Channel ferry connections.
-
C.
Honfleur
Honfleur is a historic port town in Normandy, northern France, renowned for its picturesque old harbor, timber-framed houses, and association with Impressionist painters.
-
D.
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.
-
E.
Port of Le Havre
The Port of Le Havre is one of France’s largest and busiest seaports, serving as a major gateway for maritime trade on the English Channel and the North Sea.
- 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_69a493494ec48190ae6751683625a9ba |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a532dd708190ab91e515a07b441e |
completed | March 1, 2026, 8:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a63755d1f081909f214ab8d497f096 |
completed | March 3, 2026, 1:20 a.m. |
Created at: March 1, 2026, 7:36 p.m.