Triple
T4543358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meuse-Argonne American Cemetery |
E109988
|
entity |
| Predicate | largestAmericanWWICemeteryInEurope |
P57616
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Meuse-Argonne American Cemetery, largestAmericanWWICemeteryInEurope, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: largestAmericanWWICemeteryInEurope Context triple: [Meuse-Argonne American Cemetery, largestAmericanWWICemeteryInEurope, true]
-
A.
isSecondLargestCemeteryIn
Indicates that a cemetery is the second largest (by size or capacity) among all cemeteries within a specified geographic area.
-
B.
numberOfCemeteries
Indicates the count of cemeteries associated with a given entity or within a specified area.
-
C.
countryOfBurial
Indicates the country in which a person or entity is buried.
-
D.
UScasualties
Indicates the number or occurrence of casualties suffered by the United States in a given conflict, event, or situation.
-
E.
hasMassGraveOf
Indicates that a location or site contains a mass grave in which the referenced individuals or remains are buried.
- 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_69bd4412524c8190be5bcc9ddee91848 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57d517e881909c3d23ed4453b0a7 |
completed | March 20, 2026, 2:21 p.m. |
| PD | Predicate disambiguation | batch_69bd5220e40481908ca2d7e2c43d8531 |
completed | March 20, 2026, 1:56 p.m. |
| PDg | Predicate description generation | batch_69bd56f6e75481909c487a94a2c2d0ba |
completed | March 20, 2026, 2:17 p.m. |
Created at: March 20, 2026, 1:05 p.m.