Triple
T13997359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Eligius Hospital |
E336733
|
entity |
| Predicate | usedAsDeviceFor |
P112092
|
FINISHED |
| Object | social commentary on American healthcare |
—
|
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: social commentary on American healthcare | Statement: [St. Eligius Hospital, usedAsDeviceFor, social commentary on American healthcare]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedAsDeviceFor Context triple: [St. Eligius Hospital, usedAsDeviceFor, social commentary on American healthcare]
-
A.
usesDevice
Indicates that one entity operates, employs, or relies on a particular device to perform an action or achieve a purpose.
-
B.
usedInDeviceFamily
Indicates that something (such as a component, technology, or feature) is employed or incorporated within a particular family of related devices.
-
C.
usedInDeviceModel
Indicates that something (such as a component, material, or technology) is utilized within or incorporated into a particular device model.
-
D.
usedOn
Indicates that one entity is applied to, operated on, or otherwise utilized in relation to another entity.
-
E.
usedBySystem
Indicates that something is utilized or operated by a particular system.
- 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_69d81c645c5c8190b1fd16a285a1b78a |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2eb68ba88190bfaf10777d607bf3 |
completed | April 14, 2026, 12:10 p.m. |
| PD | Predicate disambiguation | batch_69dd465dfbc4819090d8c61fd572d35f |
completed | April 13, 2026, 7:39 p.m. |
| PDg | Predicate description generation | batch_69de01ed2098819088ec45069f6f2609 |
completed | April 14, 2026, 8:59 a.m. |
Created at: April 9, 2026, 10:19 p.m.