Triple
T17273781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bessin |
E419332
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Port-en-Bessin-Huppain |
E443265
|
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: Port-en-Bessin-Huppain | Statement: [Bessin, contains, Port-en-Bessin-Huppain]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Port-en-Bessin-Huppain Context triple: [Bessin, contains, Port-en-Bessin-Huppain]
-
A.
Port-en-Bessin-Huppain
chosen
Port-en-Bessin-Huppain is a coastal commune in Normandy, France, known for its fishing harbor and its location near the historic D-Day landing beaches.
-
B.
Secqueville-en-Bessin
Secqueville-en-Bessin is a small commune in the Calvados department of the Normandy region in northwestern France.
-
C.
Beaumont-sur-Mer
Beaumont-sur-Mer is a fictional upscale seaside town that serves as the primary setting for the film "Bedtime Story."
-
D.
Hautot-sur-Mer
Hautot-sur-Mer is a coastal commune in northern France, near Dieppe, known for its World War II history and military cemetery commemorating Canadian soldiers.
-
E.
Cayeux-sur-Mer
Cayeux-sur-Mer is a coastal commune in northern France known for its long pebble beach and traditional wooden beach huts along the English Channel.
- 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_69d886da626481908a14ce7830329a35 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42f4c209c81909c713ed78f2cb19a |
completed | April 19, 2026, 1:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01794d605481908b5e430c3142c203 |
completed | May 11, 2026, 6:38 a.m. |
Created at: April 10, 2026, 5:40 a.m.