Triple
T5253713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woodlawn National Cemetery |
E118647
|
entity |
| Predicate | hasApproximateBurialCount |
P14555
|
FINISHED |
| Object | over 10,000 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: over 10,000 burials | Statement: [Woodlawn National Cemetery, hasApproximateBurialCount, over 10,000 burials]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateBurialCount Context triple: [Woodlawn National Cemetery, hasApproximateBurialCount, over 10,000 burials]
-
A.
numberOfBurials
chosen
Indicates the total count of burial events associated with a given entity.
-
B.
hasApproximateNumberOfTombs
Indicates that an entity is associated with a tomb count that is approximate rather than exact.
-
C.
hasBurialsFrom
Indicates that a location or site contains burials originating from a specified time period, culture, or source.
-
D.
burialsUntil
Indicates the number of burial events that remain or are scheduled to occur up to a specified point in time or condition.
-
E.
cemeteryBurialsSince
Indicates the number of burials that have occurred in a cemetery from a specified point in time onward.
- 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_69bd446978108190bb5f9c5c23d93f88 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7ba1cca88190bebd516851b9bf7f |
completed | March 20, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69bd77c30bac8190a883ca45da35d667 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:50 p.m.