Triple
T4085035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NYC Health + Hospitals facilities |
E87569
|
entity |
| Predicate | publicHealthcareSystem |
P7500
|
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: [NYC Health + Hospitals facilities, publicHealthcareSystem, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: publicHealthcareSystem Context triple: [NYC Health + Hospitals facilities, publicHealthcareSystem, yes]
-
A.
healthSystem
Indicates a relationship where an entity functions as, belongs to, or is managed within a particular health care system or network.
-
B.
positionOnHealthCare
Indicates a person or entity’s stance, opinion, or policy preference regarding health care systems, services, or reforms.
-
C.
publicHealthResponse
Indicates actions and measures taken by authorities or organizations to prevent, control, or mitigate health threats within a population.
-
D.
healthcareType
chosen
Indicates the category or kind of healthcare service, system, or coverage associated with an entity.
-
E.
electronicHealthRecordSystem
Indicates a relationship where an entity functions as or is associated with an electronic system used to create, store, manage, or access patients’ health records.
- 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_69aed9435cf48190ad1da737c962d19d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefc7b7cc4819089cfbf2b1c23ccc5 |
completed | March 9, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69aef9082c2081908474f082a49bebc8 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:39 p.m.