Triple
T1074347
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Normandy |
E23801
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Bayeux |
E105080
|
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: Bayeux | Statement: [Normandy, contains, Bayeux]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bayeux Context triple: [Normandy, contains, Bayeux]
-
A.
Bayeux
chosen
Bayeux is a historic town in Normandy, France, renowned for the medieval Bayeux Tapestry and its proximity to the D-Day landing beaches.
-
B.
Calais
Calais is a major French port city on the northern coast, serving as one of the primary crossing points between France and England.
-
C.
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.
-
D.
Caen
Caen is a historic city in Normandy, France, known for its medieval architecture, ties to William the Conqueror, and its role in the World War II Normandy campaign.
-
E.
Reims
Reims is a historic city in northeastern France known for its Gothic cathedral, role in French coronations, and significance during both World Wars.
- 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_69a493f1ddf48190a99d54b00e99f8ce |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b92cbfd481909e2f928c1d06ebaa |
completed | March 1, 2026, 10:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac5ea491ec8190bf6bd84ecb5af341 |
completed | March 7, 2026, 5:21 p.m. |
Created at: March 1, 2026, 7:42 p.m.