Triple
T30613897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Where the Heart Is |
E779260
|
entity |
| Predicate | hasTypeOfNurse |
P140593
|
FINISHED |
| Object | district nurse |
—
|
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: district nurse | Statement: [Where the Heart Is, hasTypeOfNurse, district nurse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfNurse Context triple: [Where the Heart Is, hasTypeOfNurse, district nurse]
-
A.
hasNurse
Indicates that an entity is assigned or associated with a nurse who provides care or medical support to it.
-
B.
practitionerType
chosen
Indicates the specific category or role of practitioner associated with an entity (e.g., doctor, nurse, therapist).
-
C.
hasWorkforceType
Indicates the type or category of workforce associated with an entity (such as permanent, temporary, contract, or part-time).
-
D.
isOccupationalFormOf
Indicates that one occupation is a specific form, variant, or specialization of another, more general occupation.
-
E.
hasSpecialist
Indicates that one entity is associated with or assigned to a specialist entity that provides expert support, service, or oversight for 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_69f224a3307081909a6dca8ca75dbf48 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fe30bc64308190b603ff1b30c2aeee |
completed | May 8, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69fe2f7175b081908dd61e1513620bbe |
completed | May 8, 2026, 6:46 p.m. |
Created at: April 29, 2026, 8:26 p.m.