Triple
T19059542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Château de Falaise |
E466488
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Caen |
—
|
NE NERFINISHED |
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 | Statement: [Château de Falaise, near, Caen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caen Context triple: [Château de Falaise, near, Caen]
-
A.
Caen
chosen
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.
-
B.
Saint-Lô
Saint-Lô is a historic town in northwestern France, known for its heavy destruction during World War II and its role as an administrative and commercial center in the Normandy region.
-
C.
Cherbourg
Cherbourg is a major French port city on the Cotentin Peninsula, known for its strategic naval harbor and cross-Channel ferry connections.
-
D.
Cherbourg
Cherbourg is a rural Aboriginal community in southern Queensland, Australia, known for its significant Indigenous history and culture.
-
E.
Arromanches-les-Bains
Arromanches-les-Bains is a coastal town in Normandy, France, best known for its role in the D-Day landings and the remains of the Mulberry artificial harbor just offshore.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dd040fb881909af2a964f65ad208 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5dc08572c8190af2f8bcfe9d1616c |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 10, 2026, 12:03 p.m.