Triple
T24072244
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacqueline Cruz |
E596264
|
entity |
| Predicate | hospitalizedFor |
P154750
|
FINISHED |
| Object | COVID-19 |
—
|
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: COVID-19 | Statement: [Jacqueline Cruz, hospitalizedFor, COVID-19]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hospitalizedFor Context triple: [Jacqueline Cruz, hospitalizedFor, COVID-19]
-
A.
hospitalizedIn
Indicates that a person or patient is admitted for medical care and staying as an inpatient in a specified hospital or healthcare facility.
-
B.
requiresQualifyingHospitalStayFor
Indicates that one entity must have a prior qualifying hospital stay as a prerequisite condition for another entity (such as a service, benefit, or coverage) to apply.
-
C.
numberOfHospitalized
Indicates the count of individuals who have been admitted to a hospital for medical care.
-
D.
containsHospital
Indicates that one entity includes or encompasses a hospital within its boundaries or composition.
-
E.
admittedTo
Indicates that one entity has been formally accepted, enrolled, or granted entry into another entity, such as an institution, program, or facility.
- 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_69e288c3999c8190809b282a04813dec |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1db1aad248190a1d25c64cc5016eb |
completed | April 29, 2026, 10:19 a.m. |
| PD | Predicate disambiguation | batch_69f1764b1d4c8190b12590c6339c31c1 |
completed | April 29, 2026, 3:08 a.m. |
| PDg | Predicate description generation | batch_69f1785afe3c81909be28986ffe944bf |
completed | April 29, 2026, 3:17 a.m. |
Created at: April 17, 2026, 10:42 p.m.