Triple
T705205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beth Israel Deaconess Medical Center |
E14082
|
entity |
| Predicate | hasOutpatientClinics |
P12416
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Beth Israel Deaconess Medical Center, hasOutpatientClinics, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOutpatientClinics Context triple: [Beth Israel Deaconess Medical Center, hasOutpatientClinics, yes]
-
A.
hasMedicalCenter
Indicates that an entity possesses, hosts, or is associated with a medical center facility.
-
B.
hasFacilities
chosen
Indicates that an entity possesses, provides, or is equipped with certain facilities or physical resources.
-
C.
hasTertiaryCareCapabilities
Indicates that an entity (such as a healthcare facility) possesses the advanced resources, specialties, and infrastructure required to provide tertiary-level medical care.
-
D.
operatedHospitalsIn
Indicates that an entity managed or ran the operations of one or more hospitals located in a specified place or context.
-
E.
containsMedicalDistrict
Indicates that one administrative or geographic area includes a designated medical district within its boundaries.
- 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_69a493494ec48190ae6751683625a9ba |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a58d4c3c8190ad4527d14bca5e6e |
completed | March 1, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69a4a4edc33881909a978268f6dd5d82 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:36 p.m.