Triple
T31492724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SPCK |
E803450
|
entity |
| Predicate | hasCharityNumberCountry |
P172266
|
FINISHED |
| Object | England and Wales |
—
|
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: England and Wales | Statement: [SPCK, hasCharityNumberCountry, England and Wales]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCharityNumberCountry Context triple: [SPCK, hasCharityNumberCountry, England and Wales]
-
A.
hasCharityRegistration
Indicates that an entity is officially registered as a charity with the relevant regulatory or governmental authority.
-
B.
charityNumber
Indicates that an entity is associated with a specific registered charity identification number.
-
C.
charitableRegistrationCountry
chosen
Indicates the country in which a charitable organization is officially registered.
-
D.
isCharity
Indicates that an entity operates as a charitable organization or is recognized as a charity.
-
E.
hasCharityConnection
Indicates a relationship in which one entity is connected to another through charitable activities, support, or affiliation.
- 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_69f348ca04508190ba9379b5329dfd75 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fd7e364a648190a1e9e1d9fc76e99e |
completed | May 8, 2026, 6:09 a.m. |
| PD | Predicate disambiguation | batch_69fd7bb547608190a3b04dddbca6b8bc |
completed | May 8, 2026, 5:59 a.m. |
Created at: April 30, 2026, 9:39 p.m.