Triple
T3965907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Normandy American Cemetery and Memorial |
E92215
|
entity |
| Predicate | primaryNationalityOfBurials |
P53655
|
FINISHED |
| Object | American |
—
|
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 | Statement: [Normandy American Cemetery and Memorial, primaryNationalityOfBurials, American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryNationalityOfBurials Context triple: [Normandy American Cemetery and Memorial, primaryNationalityOfBurials, American]
-
A.
countryOfBurial
Indicates the country in which a person or entity is buried.
-
B.
eraOfMostBurials
Indicates the historical time period during which the greatest number of burials occurred for a given site or context.
-
C.
hasBurialsFrom
Indicates that a location or site contains burials originating from a specified time period, culture, or source.
-
D.
burialPlace
Indicates the location where a person or entity is buried.
-
E.
originalNationality
Indicates the country or nationality an entity initially belonged to or originated from, before any later changes in citizenship or affiliation.
- F. None of above. chosen
Provenance (4 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_69aed96624188190ac8c45bb57ab72b5 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefba878a48190a2e234d775215938 |
completed | March 9, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69aef8efcf3c81908ccf61d9ce26b0c0 |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aefba6b9848190a7b0fb66100a2a0c |
completed | March 9, 2026, 4:56 p.m. |
Created at: March 9, 2026, 3:32 p.m.