Triple
T7512964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VA Medical Center Philadelphia |
E177566
|
entity |
| Predicate | primaryPopulationServed |
P17586
|
FINISHED |
| Object | adult patients |
—
|
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: adult patients | Statement: [VA Medical Center Philadelphia, primaryPopulationServed, adult patients]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryPopulationServed Context triple: [VA Medical Center Philadelphia, primaryPopulationServed, adult patients]
-
A.
targetedPopulation
chosen
Indicates the group of individuals or entities that an action, intervention, or effect is specifically directed toward.
-
B.
primaryServes
Indicates that one entity’s main or principal function is to serve, support, or provide service to another entity.
-
C.
organizationTypeServed
Indicates the type of organization that is served or supported by a given entity or activity.
-
D.
professionServed
Indicates that an entity has performed work or provided services in a particular profession or occupational role.
-
E.
hasServiceAreaPopulation
Indicates that an entity has a service area characterized by a specific population size or count.
- 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_69c69f276b108190af2cc790b6554544 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f5d52b2c8190ba32b1575756fa7c |
completed | March 27, 2026, 9:25 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d44e9481909813e073b194f6f4 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:45 p.m.