Triple
T13089217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evergreen Cemetery, Gettysburg, Pennsylvania |
E310415
|
entity |
| Predicate | hasNotableBurial |
P196
|
FINISHED |
| Object | James A. Beaver |
—
|
NE NERFINISHED |
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: James A. Beaver | Statement: [Evergreen Cemetery, Gettysburg, Pennsylvania, hasNotableBurial, James A. Beaver]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: James A. Beaver Context triple: [Evergreen Cemetery, Gettysburg, Pennsylvania, hasNotableBurial, James A. Beaver]
-
A.
James A. Beaver
chosen
James A. Beaver was a 19th-century American politician and Civil War general who served as governor of Pennsylvania.
-
B.
John M. Bevan
John M. Bevan was an American educator best known for founding Eckerd College in Florida.
-
C.
Thomas H. Beck
Thomas H. Beck was an American magazine publisher and civic leader best known for helping establish the Civil Air Patrol during World War II.
-
D.
Samuel E. Beetley
Samuel E. Beetley was a film editor best known for his work on the epic World War II film "The Longest Day."
-
E.
James B. Beck
James B. Beck was a 19th-century Scottish-born American politician who served as a U.S. Representative and Senator from Kentucky.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d806a733548190989cfd4ce981ca33 |
completed | April 9, 2026, 8:05 p.m. |
| NER | Named-entity recognition | batch_69d98138a1d481908a139f2f67eb3472 |
completed | April 10, 2026, 11:01 p.m. |
Created at: April 9, 2026, 9:03 p.m.