Triple
T37099020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maimonides Medical Center |
E918643
|
entity |
| Predicate | hasEmergencyMedicineDepartment |
P59476
|
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: [Maimonides Medical Center, hasEmergencyMedicineDepartment, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEmergencyMedicineDepartment Context triple: [Maimonides Medical Center, hasEmergencyMedicineDepartment, yes]
-
A.
hasEmergencyDepartmentLevel
Indicates the specific classification or tier of emergency care capability associated with an emergency department.
-
B.
hasEmergencyCare
chosen
Indicates that an entity provides or is equipped with emergency medical care services for another entity or individuals.
-
C.
emergencyDepartment
Indicates that an entity is associated with, located in, or functions as an emergency department within a healthcare or medical context.
-
D.
hasTraumaCenter
Indicates that an entity (such as a hospital or facility) includes or is equipped with a designated trauma center capable of providing specialized emergency care for severe injuries.
-
E.
hasEmergencyServiceProvider
Indicates that an entity is associated with or served by a specific emergency service provider (such as police, fire, or medical services).
- 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_69f76e9a48bc8190a3947508d8bca408 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb344c60f8819090f2e21e1e61d621 |
completed | May 6, 2026, 12:30 p.m. |
| PD | Predicate disambiguation | batch_69fb2f642db08190b562725502c74ea6 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 3, 2026, 4:14 p.m.