Triple
T35745509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Twelve Patients: Life and Death at Bellevue Hospital |
E1033166
|
entity |
| Predicate | numberOfPatientsDescribed |
P206030
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [Twelve Patients: Life and Death at Bellevue Hospital, numberOfPatientsDescribed, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPatientsDescribed Context triple: [Twelve Patients: Life and Death at Bellevue Hospital, numberOfPatientsDescribed, 12]
-
A.
numberOfDescribedDrugs
Indicates the quantity of drugs that are being described or specified in a given context.
-
B.
numberOfHospitalized
Indicates the count of individuals who have been admitted to a hospital for medical care.
-
C.
numberOfSystemsDescribed
Indicates the total count of distinct systems that are described or referenced in relation to a given subject.
-
D.
numberOfAnnualPatientVisits
Indicates the total count of patient visits that occur over the course of one year.
-
E.
representsToPatients
Indicates that an entity serves as a representative or acts on behalf of patients in some context or interaction.
- 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_69f76e119d508190a3873cb302063832 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037ce70f54819082946dad8d380825 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a069e6c8190857b611fffb7b867 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037ce53de881908cf14141cf3bc570 |
completed | May 12, 2026, 7:17 p.m. |
Created at: May 3, 2026, 4:06 p.m.