Triple
T11865102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrew Lansley |
E282259
|
entity |
| Predicate | legislativeInterest |
P17365
|
FINISHED |
| Object | health services |
—
|
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: health services | Statement: [Andrew Lansley, legislativeInterest, health services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legislativeInterest Context triple: [Andrew Lansley, legislativeInterest, health services]
-
A.
legislativeActivity
Indicates involvement in creating, debating, amending, or passing laws or related legislative measures.
-
B.
sharesLegislativeRepresentationIn
Indicates that two or more entities are represented by the same legislative body, district, or representative within a political system.
-
C.
areaOfLegislation
chosen
Indicates that one entity defines, concerns, or governs the legal domain or subject matter covered by another entity.
-
D.
relatedLegislation
Indicates that there exists a legislative document that is connected to, affects, or is otherwise relevant to the subject entity.
-
E.
signedLegislation
Indicates that an authority formally approved and enacted a piece of legislation into law by signing it.
- 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a73883508190a78b5f4ba4a220df |
completed | April 10, 2026, 7:31 a.m. |
| PD | Predicate disambiguation | batch_69d8a2589f0c8190ad82ff11acabae93 |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:43 p.m.