Triple
T2196543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calvary Cemetery (St. Louis) |
E49986
|
entity |
| Predicate | hasApproximateNumberOfBurials |
P14555
|
FINISHED |
| Object | over 300000 |
—
|
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: over 300000 | Statement: [Calvary Cemetery (St. Louis), hasApproximateNumberOfBurials, over 300000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateNumberOfBurials Context triple: [Calvary Cemetery (St. Louis), hasApproximateNumberOfBurials, over 300000]
-
A.
numberOfBurials
chosen
Indicates the total count of burial events associated with a given entity.
-
B.
hasNotableBurials
Indicates that a place, typically a cemetery or burial site, contains the graves or remains of individuals considered notable or significant.
-
C.
cemeteryBurialsSince
Indicates the number of burials that have occurred in a cemetery from a specified point in time onward.
-
D.
eraOfMostBurials
Indicates the historical time period during which the greatest number of burials occurred for a given site or context.
-
E.
hasTypeOfBurial
Indicates the specific kind or method of burial associated with an entity.
- 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_69a88aaba3c48190b351cab9b26989ff |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbf77e4f08190a1f5ea601d306596 |
completed | March 7, 2026, 6:02 a.m. |
| PD | Predicate disambiguation | batch_69abbda52328819089c7ab111bebb0ca |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.