Triple
T11515369
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Tor |
E273016
|
entity |
| Predicate | typicalClinicalSeverity |
P99893
|
FINISHED |
| Object | milder than classical cholera |
—
|
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: milder than classical cholera | Statement: [El Tor, typicalClinicalSeverity, milder than classical cholera]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalClinicalSeverity Context triple: [El Tor, typicalClinicalSeverity, milder than classical cholera]
-
A.
typicalComplexity
Indicates the usual or characteristic level of complexity associated with an entity, process, or situation.
-
B.
fastSeverity
Indicates the level or intensity of severity associated with something that is fast or time-critical.
-
C.
typicalAdmission
Indicates that an entity is a standard or commonly expected type of admission associated with another entity (such as an institution, event, or program).
-
D.
accidentSeverity
Indicates the level or degree of seriousness associated with an accident.
-
E.
hasClinicalSignificance
Indicates that something (such as a finding, variant, or condition) has a meaningful impact or relevance in a clinical or medical context.
- 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_69d6aae2c3748190bed2ea50dfb160dc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d86db8bf9c8190820c289e6b0c3873 |
completed | April 10, 2026, 3:25 a.m. |
| PD | Predicate disambiguation | batch_69d80876e5f0819088cff2e72f773cf6 |
completed | April 9, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69d822ef46988190a1c360da4ee14fef |
completed | April 9, 2026, 10:06 p.m. |
Created at: April 8, 2026, 9:36 p.m.