Triple
T4296591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colleville-sur-Mer |
E99727
|
entity |
| Predicate | hasWarGraves |
P36715
|
FINISHED |
| Object | American soldiers of World War II |
—
|
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: American soldiers of World War II | Statement: [Colleville-sur-Mer, hasWarGraves, American soldiers of World War II]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWarGraves Context triple: [Colleville-sur-Mer, hasWarGraves, American soldiers of World War II]
-
A.
hasMassGraveOf
Indicates that a location or site contains a mass grave in which the referenced individuals or remains are buried.
-
B.
hasNotableBurials
Indicates that a place, typically a cemetery or burial site, contains the graves or remains of individuals considered notable or significant.
-
C.
hasBurialsFrom
Indicates that a location or site contains burials originating from a specified time period, culture, or source.
-
D.
hasBurialsFromConflict
chosen
Indicates that the subject location or site contains burials that originated as a result of a specific conflict or violent event.
-
E.
numberOfBurials
Indicates the total count of burial events associated with a given entity.
- 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_69b3455175088190aa79c6e03b86647e |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3509aebd48190af38f2e37f07869a |
completed | March 12, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69b347fe55a88190b77bab0c0f38e1aa |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:08 p.m.