Triple
T3498831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Birmingham Cathedral |
E73914
|
entity |
| Predicate | hasChurchyardUse |
P48762
|
FINISHED |
| Object | public open space |
—
|
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: public open space | Statement: [Birmingham Cathedral, hasChurchyardUse, public open space]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChurchyardUse Context triple: [Birmingham Cathedral, hasChurchyardUse, public open space]
-
A.
hasCemetery
Indicates that one entity possesses, contains, or includes a cemetery associated with it.
-
B.
isCemeteryFor
Indicates that one entity serves as the burial ground designated for another entity, such as a community, group, or location.
-
C.
usedAsCemeterySince
Indicates that a place has functioned as a cemetery starting from a specified point in time.
-
D.
hasNearbyCemetery
Indicates that one entity is located close to, or in the immediate vicinity of, a cemetery associated with another entity.
-
E.
usedForBurialOf
Indicates that something serves or is employed as a means, place, or object for burying a particular entity.
- 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_69ad85cdb6e48190a335d412b9194ed8 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbbd3ad548190abbfae820bf3b66d |
completed | March 8, 2026, 6:11 p.m. |
| PD | Predicate disambiguation | batch_69adae0b34908190b2bb5766a2231f7a |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adb055ed2481908171effe28151cf9 |
completed | March 8, 2026, 5:22 p.m. |
Created at: March 8, 2026, 3:18 p.m.