Triple
T21091971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Specially Adapted Housing grants |
E519658
|
entity |
| Predicate | targetDisabilities |
P63365
|
FINISHED |
| Object | loss or loss of use of both legs |
—
|
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: loss or loss of use of both legs | Statement: [Specially Adapted Housing grants, targetDisabilities, loss or loss of use of both legs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetDisabilities Context triple: [Specially Adapted Housing grants, targetDisabilities, loss or loss of use of both legs]
-
A.
disabilityCategories
chosen
Indicates that there is a relationship specifying which disability category or categories are associated with a given entity.
-
B.
causeOfDisability
Indicates that one entity is the reason or source that brings about another entity’s disability.
-
C.
disability
Indicates that an entity has a physical, mental, or sensory impairment that substantially limits one or more major life activities.
-
D.
viewOnDisability
Indicates the stance, perspective, or attitude an entity holds toward disability or disabled individuals.
-
E.
hasDisabilityRepresentation
Indicates that something includes, portrays, or accounts for the presence and experiences of people with disabilities.
- 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_69e0b507dd9081908fb8bfcbef4c8b46 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7094f6ebc8190a90b014755a9d4a6 |
completed | April 21, 2026, 5:21 a.m. |
| PD | Predicate disambiguation | batch_69e5dbfcd5e881908f1e4e0d2d237856 |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 2:51 p.m.