Triple
T12194705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London Necropolis |
E290556
|
entity |
| Predicate | burialGroundCapacity |
P104246
|
FINISHED |
| Object | very large cemetery capacity at Brookwood |
—
|
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: very large cemetery capacity at Brookwood | Statement: [London Necropolis, burialGroundCapacity, very large cemetery capacity at Brookwood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: burialGroundCapacity Context triple: [London Necropolis, burialGroundCapacity, very large cemetery capacity at Brookwood]
-
A.
numberOfBurials
Indicates the total count of burial events associated with a given entity.
-
B.
hasCemetery
Indicates that one entity possesses, contains, or includes a cemetery associated with it.
-
C.
eraOfMostBurials
Indicates the historical time period during which the greatest number of burials occurred for a given site or context.
-
D.
burialPlace
Indicates the location where a person or entity is buried.
-
E.
numberOfCemeteries
Indicates the count of cemeteries associated with a given entity or within a specified area.
- 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_69d6ab64de5881908d56eb7a75c6cc69 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d938cd2edc8190b1971349dbc0dee0 |
completed | April 10, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69d91c38321c819080d500d0d64a04f6 |
completed | April 10, 2026, 3:50 p.m. |
| PDg | Predicate description generation | batch_69d938ca32908190bd56f563efcbe8a0 |
completed | April 10, 2026, 5:52 p.m. |
Created at: April 8, 2026, 9:50 p.m.