Triple
T38692927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Territories East Cluster |
E949919
|
entity |
| Predicate | hasOutpatientFacility |
P82392
|
FINISHED |
| Object | various general outpatient clinics |
—
|
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: various general outpatient clinics | Statement: [New Territories East Cluster, hasOutpatientFacility, various general outpatient clinics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOutpatientFacility Context triple: [New Territories East Cluster, hasOutpatientFacility, various general outpatient clinics]
-
A.
hasAmbulatory
chosen
Indicates that an entity possesses or is provided with ambulatory (walking or outpatient) capabilities or services.
-
B.
hasFacilityLocation
Indicates that an entity possesses or is associated with a facility situated at a specific location.
-
C.
hasMedicalCenter
Indicates that an entity possesses, hosts, or is associated with a medical center facility.
-
D.
hasHealthCareInstitutionType
Indicates that an entity is classified as a specific type or category of healthcare institution.
-
E.
hasHospitalType
Indicates that a hospital is classified as belonging to a specific type or category (e.g., general, specialized, teaching).
- 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_69f76f0124408190bb39c3040734846b |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fce545fec881909247a3af821d21ae |
completed | May 7, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69fce12eaeec81908cf81346b2cef6e0 |
completed | May 7, 2026, 6:59 p.m. |
Created at: May 3, 2026, 4:33 p.m.