Triple
T26459397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bény-sur-Mer |
E665586
|
entity |
| Predicate | hasCemeteryFor |
P1496
|
FINISHED |
| Object | Canadian soldiers |
—
|
LITERAL 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: Canadian soldiers | Statement: [Bény-sur-Mer, hasCemeteryFor, Canadian soldiers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCemeteryFor Context triple: [Bény-sur-Mer, hasCemeteryFor, Canadian soldiers]
-
A.
hasCemetery
chosen
Indicates that one entity possesses, contains, or includes a cemetery associated with it.
-
B.
isCemeteryFor
Indicates that one entity serves as the burial ground designated for another entity, such as a community, group, or location.
-
C.
hasNearbyCemetery
Indicates that one entity is located close to, or in the immediate vicinity of, a cemetery associated with another entity.
-
D.
hasCemeteryFeature
Indicates that a cemetery possesses or is characterized by a specific feature or attribute.
-
E.
associatedCemetery
Indicates that there is a relationship linking an entity (such as a person, event, or organization) to a specific cemetery with which it is connected.
- F. None of above.
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_69ee883e812c8190a9b5a9cdb87fee5e |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f67257b0448190a13011af81c81449 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 27, 2026, 12:11 a.m.