Triple
T25434351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ryan White Part F |
E637335
|
entity |
| Predicate | populationHealthGoal |
P102263
|
FINISHED |
| Object | reduce disparities in access to HIV 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: reduce disparities in access to HIV care | Statement: [Ryan White Part F, populationHealthGoal, reduce disparities in access to HIV care]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationHealthGoal Context triple: [Ryan White Part F, populationHealthGoal, reduce disparities in access to HIV care]
-
A.
publicHealthDomain
Indicates that something is related to, situated within, or primarily concerned with the field of public health.
-
B.
healthTheme
Indicates that the subject is associated with, focuses on, or is characterized by a particular health-related topic or theme.
-
C.
targetedPopulation
Indicates the group of individuals or entities that an action, intervention, or effect is specifically directed toward.
-
D.
hasHealthGoal
chosen
Indicates that an entity has a specific health-related objective or target it is aiming to achieve.
-
E.
healthDisparityAddressed
Indicates that actions, interventions, or policies are aimed at reducing or eliminating inequities in health outcomes between different populations or groups.
- 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_69e75db6c97081908178383fa632b193 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f6dd99f88190848a5bbee795aa17 |
completed | May 2, 2026, 1:06 p.m. |
| PD | Predicate disambiguation | batch_69f5afd5baac8190bb8ed576813c8591 |
completed | May 2, 2026, 8:03 a.m. |
Created at: April 21, 2026, 1:59 p.m.