Triple
T9457679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Medicare Part A |
E228058
|
entity |
| Predicate | coversSetting |
P89047
|
FINISHED |
| Object | acute care hospitals |
—
|
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: acute care hospitals | Statement: [Medicare Part A, coversSetting, acute care hospitals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coversSetting Context triple: [Medicare Part A, coversSetting, acute care hospitals]
-
A.
setting
Indicates the place, time, or context in which an event, action, or interaction occurs.
-
B.
featuresSetting
Indicates that something includes, presents, or highlights a particular setting as a notable or primary aspect.
-
C.
notableSetting
Indicates that a particular place or environment is especially significant or prominent as the context in which an entity is situated or occurs.
-
D.
usedAsSettingFor
Indicates that one entity serves as the backdrop, location, or environment in which another entity (such as an event, story, or activity) takes place.
-
E.
secondarySetting
Indicates that an entity serves as an additional or supporting setting context for another entity, rather than being the primary setting.
- F. None of above. chosen
Provenance (4 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_69ca843b123881909b0e60028475d12d |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7f90cf648190ab238ba6b4f03c4f |
completed | April 1, 2026, 8:26 p.m. |
| PD | Predicate disambiguation | batch_69cca55caaa8819089c5138e014892d3 |
completed | April 1, 2026, 4:55 a.m. |
| PDg | Predicate description generation | batch_69ccbf9b080c819098934a18cf2bac5d |
completed | April 1, 2026, 6:47 a.m. |
Created at: March 30, 2026, 7:52 p.m.