Triple
T28604860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dibley parish church |
E724015
|
entity |
| Predicate | fictionalDenomination |
P184364
|
FINISHED |
| Object | Church of England |
—
|
NE NERFINISHED |
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: Church of England | Statement: [Dibley parish church, fictionalDenomination, Church of England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalDenomination Context triple: [Dibley parish church, fictionalDenomination, Church of England]
-
A.
fictionalDiocese
Indicates that a diocese mentioned in a context is not a real, historically existing ecclesiastical jurisdiction but one that is invented or imaginary.
-
B.
fictionalType
Indicates that one entity is a fictional or imaginary type or category of the other entity.
-
C.
fictionalOrigin
Indicates that one entity originates from, or was first introduced within, a fictional work, universe, or narrative created by another entity.
-
D.
fictionalSon
Indicates that one entity is portrayed as the son of another entity within a fictional or narrative context.
-
E.
fictionalUse
Indicates that one entity makes use of another within a fictional or imaginary context, rather than in real-world usage.
- 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_69f01d816d7c8190a1fe27e3434041dc |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f7b0e5744c8190a22c1e1d6fcfa466 |
completed | May 3, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f7ab70d034819080295628497d8582 |
completed | May 3, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69f7b0e3917481908a394680d76743c3 |
completed | May 3, 2026, 8:32 p.m. |
Created at: April 28, 2026, 4:26 a.m.