Triple
T9561311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Education Authority (Northern Ireland) |
E230679
|
entity |
| Predicate | hasNumberOfRegionalOffices |
P89796
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Education Authority (Northern Ireland), hasNumberOfRegionalOffices, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfRegionalOffices Context triple: [Education Authority (Northern Ireland), hasNumberOfRegionalOffices, 5]
-
A.
numberOfOffices
Indicates the total count of offices associated with a given entity.
-
B.
numberOfCountryOffices
Indicates the total count of offices or branches that an organization maintains across different countries.
-
C.
hasBranchOffice
Indicates that one organization maintains a branch office or subsidiary location in another place or entity.
-
D.
mayHaveBranchOfficesIn
Indicates that an entity is permitted or allowed to establish branch offices in a specified location.
-
E.
numberOfRegionalOfficesInWHO
Indicates the total count of regional offices that an entity has within the World Health Organization (WHO) structure.
- 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_69ca847e53a88190a60eed7e02257f10 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd994d31e08190b139f5ad10d8ea31 |
completed | April 1, 2026, 10:16 p.m. |
| PD | Predicate disambiguation | batch_69ccd594d0ac8190a81bc11a3a538167 |
completed | April 1, 2026, 8:21 a.m. |
| PDg | Predicate description generation | batch_69ccd93e90048190a2b0d7c5c195ba98 |
completed | April 1, 2026, 8:37 a.m. |
Created at: March 30, 2026, 8:03 p.m.