Triple
T37099017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maimonides Medical Center |
E918643
|
entity |
| Predicate | hasPsychiatryDepartment |
P166043
|
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, hasPsychiatryDepartment, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPsychiatryDepartment Context triple: [Maimonides Medical Center, hasPsychiatryDepartment, yes]
-
A.
hasPsychiatricComponent
chosen
Indicates that something includes, involves, or is associated with a psychiatric aspect, factor, or condition as part of its overall nature or composition.
-
B.
hasPsychologicalCondition
Indicates that an entity experiences or is diagnosed with a particular psychological or mental health condition.
-
C.
hasPharmacyDepartment
Indicates that an entity includes or is associated with a dedicated pharmacy department or unit.
-
D.
hasCrisisFacility
Indicates that an entity possesses or includes a dedicated facility or service for handling crises or emergency situations.
-
E.
hasMedicalCenter
Indicates that an entity possesses, hosts, or is associated with a medical center facility.
- 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.