Triple
T11515371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Tor |
E273016
|
entity |
| Predicate | hasCaseFatalityRate |
P20197
|
FINISHED |
| Object | lower than classical biotype in treated patients |
—
|
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: lower than classical biotype in treated patients | Statement: [El Tor, hasCaseFatalityRate, lower than classical biotype in treated patients]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCaseFatalityRate Context triple: [El Tor, hasCaseFatalityRate, lower than classical biotype in treated patients]
-
A.
caseFatalityRate
chosen
Indicates the proportion of deaths among all identified cases of a particular disease or condition within a specified period.
-
B.
mortalityRate
Indicates the proportion of individuals in a defined population that die within a specified time period.
-
C.
fatalitiesCategory
Indicates the classification of deaths associated with an event, incident, or condition into a specific category or severity level.
-
D.
deathTollEstimate
Indicates an estimated number of deaths attributed to a particular event, cause, or period.
-
E.
hasCasualtiesLevel
Indicates the severity or extent of casualties associated with an event, incident, or situation.
- 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_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. |
Created at: April 8, 2026, 9:36 p.m.