Triple
T5808582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suresnes American Cemetery |
E128809
|
entity |
| Predicate | numberOfWorldWarIBurials |
P14555
|
FINISHED |
| Object | 1541 |
—
|
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: 1541 | Statement: [Suresnes American Cemetery, numberOfWorldWarIBurials, 1541]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfWorldWarIBurials Context triple: [Suresnes American Cemetery, numberOfWorldWarIBurials, 1541]
-
A.
numberOfMassGraves
Indicates the quantity of mass graves associated with or present at a given entity or location.
-
B.
numberOfBurials
chosen
Indicates the total count of burial events associated with a given entity.
-
C.
numberOfHoldersKilledInWorldWarII
Indicates the number of holders of a given title, position, or role who were killed during World War II.
-
D.
militaryCasualtiesEstimate
Indicates an estimated number of people killed, wounded, or missing as a result of military conflict or operations.
-
E.
hasBurialsFromConflict
Indicates that the subject location or site contains burials that originated as a result of a specific conflict or violent event.
- 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_69c0084788848190bcf71f6bc5d71597 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02b1867a481909a7ea3331dbb04ce |
completed | March 22, 2026, 5:47 p.m. |
| PD | Predicate disambiguation | batch_69c021d5ecd081908a62dd66e26f8598 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:52 p.m.