Triple
T29194295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harolyn Suzanne Nicholas |
E740079
|
entity |
| Predicate | careStatus |
P160817
|
FINISHED |
| Object | institutionalized for long-term 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: institutionalized for long-term care | Statement: [Harolyn Suzanne Nicholas, careStatus, institutionalized for long-term care]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: careStatus Context triple: [Harolyn Suzanne Nicholas, careStatus, institutionalized for long-term care]
-
A.
healthIndicator
Indicates a measure or signal that reflects the health status or condition of an entity.
-
B.
requiresCare
Indicates that one entity depends on another to provide care, attention, or maintenance for its proper functioning or well-being.
-
C.
saluteStatus
Indicates the type or state of a salute being given or received between entities (e.g., whether, how, or in what manner one entity salutes another).
-
D.
hasHealthCareCharacteristic
chosen
Indicates that an entity possesses a specific healthcare-related attribute, quality, or feature.
-
E.
care
Indicates showing concern, attention, or responsibility for the well-being or needs of another entity.
- 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_69f07cb8033c8190b8807e219a14333d |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f663c0a698819090eeeb219822e78a |
completed | May 2, 2026, 8:51 p.m. |
| PD | Predicate disambiguation | batch_69f65c24f8b48190af81b575f3c15be5 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 28, 2026, 12:03 p.m.