Triple
T9458856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | General Teaching Council for Northern Ireland |
E228086
|
entity |
| Predicate | typeOfRegister |
P25614
|
FINISHED |
| Object | statutory register |
—
|
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: statutory register | Statement: [General Teaching Council for Northern Ireland, typeOfRegister, statutory register]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfRegister Context triple: [General Teaching Council for Northern Ireland, typeOfRegister, statutory register]
-
A.
regulatorType
Indicates the specific kind or category of regulatory role or authority associated with an entity.
-
B.
hasRegistrationType
Indicates that an entity is associated with a specific category or type of registration it holds or requires.
-
C.
typeOf
Indicates that one entity is a specific kind, class, or category instance of another more general entity.
-
D.
registryType
chosen
Indicates the specific category or classification of a registry that an entity is associated with or recorded in.
-
E.
typicalRegister
Indicates the usual or most common linguistic register (e.g., formal, informal, technical) in which something—such as a word, expression, or communication—is typically used.
- 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_69ca843b123881909b0e60028475d12d |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7fc916348190aeb3874a89071677 |
completed | April 1, 2026, 8:27 p.m. |
| PD | Predicate disambiguation | batch_69cca55caaa8819089c5138e014892d3 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:52 p.m.