Triple
T46903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NHS organisations |
E918
|
entity |
| Predicate | serviceEligibility |
P1130
|
FINISHED |
| Object | UK residents |
—
|
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: UK residents | Statement: [NHS organisations, serviceEligibility, UK residents]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: serviceEligibility Context triple: [NHS organisations, serviceEligibility, UK residents]
-
A.
eligibility
Indicates that an entity meets the required conditions or qualifications to participate in, receive, or perform something.
-
B.
eligibilityCriteria
chosen
Indicates the conditions or requirements that must be satisfied for an entity to qualify for or be considered eligible for something.
-
C.
hasBenefit
Indicates that one entity provides an advantage, improvement, or positive outcome to another entity.
-
D.
servedByService
Indicates that something is provided, handled, or fulfilled by a particular service.
-
E.
hasServiceType
Indicates that an entity is associated with or categorized by a particular type of service.
- 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_69a2480baefc81909951b14058479aa2 |
completed | Feb. 28, 2026, 1:42 a.m. |
| NER | Named-entity recognition | batch_69a24b1bf2c081908f20e13939b713ff |
completed | Feb. 28, 2026, 1:55 a.m. |
| PD | Predicate disambiguation | batch_69a24abd07508190a83ffba5368c1c79 |
completed | Feb. 28, 2026, 1:54 a.m. |
Created at: Feb. 28, 2026, 1:47 a.m.