Triple
T19234827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gettysburg National Cemetery |
E480965
|
entity |
| Predicate | numberOfIntermentsApproximate |
P95901
|
FINISHED |
| Object | 3500 Civil War burials |
—
|
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: 3500 Civil War burials | Statement: [Gettysburg National Cemetery, numberOfIntermentsApproximate, 3500 Civil War burials]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfIntermentsApproximate Context triple: [Gettysburg National Cemetery, numberOfIntermentsApproximate, 3500 Civil War burials]
-
A.
numberOfBurials
Indicates the total count of burial events associated with a given entity.
-
B.
numberOfInterred
chosen
Indicates the total count of individuals who are buried or interred at a given site or within a specified context.
-
C.
numberOfCemeteries
Indicates the count of cemeteries associated with a given entity or within a specified area.
-
D.
cemeteryBurialsSince
Indicates the number of burials that have occurred in a cemetery from a specified point in time onward.
-
E.
numberOfCoffins
Indicates the quantity of coffins associated with a given entity or situation.
- 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_69d8e8ccb8f48190ad420098e74fb1db |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5faec6d0c8190b90cb1bb3160a847 |
completed | April 20, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e4dcfae6f081909cc173cf71a5005c |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:26 p.m.