Triple
T4406739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St Marylebone Cemetery |
E93749
|
entity |
| Predicate | hasChapelDenomination |
P45908
|
FINISHED |
| Object | Anglican |
—
|
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: Anglican | Statement: [St Marylebone Cemetery, hasChapelDenomination, Anglican]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChapelDenomination Context triple: [St Marylebone Cemetery, hasChapelDenomination, Anglican]
-
A.
hasCathedralDenomination
Indicates the religious denomination with which a cathedral is affiliated or to which it belongs.
-
B.
hasChapels
Indicates that one entity contains, includes, or is associated with one or more chapels.
-
C.
hasChapelCountApprox
Indicates an approximate number of chapels associated with an entity.
-
D.
hasChurchType
Indicates that one entity (typically a church) is classified as being of a particular church type or category.
-
E.
hasDenominationalPresence
chosen
Indicates that a particular religious denomination is present or represented within a given location, organization, or context.
- 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_69b345158c748190a2c040fce2da9980 |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b3548b1ca08190b3136867c7098d86 |
completed | March 13, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69b34f5b36a881909bf2e970aa523390 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:28 p.m.