Triple
T973992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anna M. Kross Center |
E21007
|
entity |
| Predicate | hasHealthcareService |
P7500
|
FINISHED |
| Object | mental health care |
—
|
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: mental health care | Statement: [Anna M. Kross Center, hasHealthcareService, mental health care]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHealthcareService Context triple: [Anna M. Kross Center, hasHealthcareService, mental health care]
-
A.
hasMedicalCenter
Indicates that an entity possesses, hosts, or is associated with a medical center facility.
-
B.
healthcareType
chosen
Indicates the category or kind of healthcare service, system, or coverage associated with an entity.
-
C.
hasPatient
Indicates that an action, event, or process involves a specific entity as the one undergoing or receiving its effects (the patient).
-
D.
healthSystem
Indicates a relationship where an entity functions as, belongs to, or is managed within a particular health care system or network.
-
E.
hasAffiliatedHospital
Indicates that one entity (typically a medical professional, clinic, or organization) is formally connected or associated with a particular hospital for professional or operational purposes.
- 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_69a493c2b62c8190b616351789ec47f8 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b45f28f081908d41b2d7f353708d |
completed | March 1, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a6aa2c8190aebba71320ab678f |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.