Triple
T28337301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgia Byrd |
E717710
|
entity |
| Predicate | undergoesMisdiagnosis |
P49451
|
FINISHED |
| Object | terminal illness |
—
|
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: terminal illness | Statement: [Georgia Byrd, undergoesMisdiagnosis, terminal illness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: undergoesMisdiagnosis Context triple: [Georgia Byrd, undergoesMisdiagnosis, terminal illness]
-
A.
diagnosisIsDifficult
Indicates that determining an accurate diagnosis for the condition or case is challenging or hard to achieve.
-
B.
diagnoses
Indicates that a medical professional identifies and determines the nature or cause of a condition, disease, or problem in a patient.
-
C.
oftenUndergo
Indicates that an entity frequently experiences, is subjected to, or passes through a particular process, action, or change.
-
D.
misidentifiedAs
chosen
Indicates that one entity has been incorrectly recognized, labeled, or understood as another, distinct entity.
-
E.
diagnosedWith
Indicates that a subject has been identified, typically by a medical professional, as having a particular disease or medical condition.
- 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_69eff6e9a57c8190a69c2c74b5d72119 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f7117e55908190a67105e92bc4830f |
completed | May 3, 2026, 9:12 a.m. |
| PD | Predicate disambiguation | batch_69f70f380690819090cc34763ba460ed |
completed | May 3, 2026, 9:02 a.m. |
Created at: April 28, 2026, 12:37 a.m.