Triple
T6723126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NHS Dental Exemption Certificates |
E153443
|
entity |
| Predicate | helpsPrevent |
P33311
|
FINISHED |
| Object | incorrect dental charge payments |
—
|
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: incorrect dental charge payments | Statement: [NHS Dental Exemption Certificates, helpsPrevent, incorrect dental charge payments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: helpsPrevent Context triple: [NHS Dental Exemption Certificates, helpsPrevent, incorrect dental charge payments]
-
A.
worksToPrevent
chosen
Indicates an entity actively takes measures or engages in actions to stop, reduce, or avoid the occurrence or impact of another entity or condition.
-
B.
prevented
Indicates that one entity stopped, hindered, or made it impossible for another entity or event to occur or proceed.
-
C.
especiallyHelpsWhen
Indicates that one entity is particularly beneficial or effective in assisting another entity or situation under certain conditions or circumstances.
-
D.
protects
Indicates taking action to keep someone or something safe from harm, danger, or negative effects.
-
E.
helpedSecure
Indicates that one entity contributed to obtaining, protecting, or ensuring the safety or stability of another entity or outcome.
- 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_69c6880afb988190ad88011b48ecfcba |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d354177481908ab3cf5437c095e2 |
completed | March 27, 2026, 6:58 p.m. |
| PD | Predicate disambiguation | batch_69c6d08e8a2c8190ae4e8d8c039be7ce |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:08 p.m.