Triple
T11515370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Tor |
E273016
|
entity |
| Predicate | typicalDehydrationSeverity |
P20959
|
FINISHED |
| Object | often less severe 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: often less severe than classical cholera | Statement: [El Tor, typicalDehydrationSeverity, often less severe than classical cholera]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalDehydrationSeverity Context triple: [El Tor, typicalDehydrationSeverity, often less severe than classical cholera]
-
A.
wetnessLevel
Indicates the degree or intensity of how wet something is in relation to a reference state or scale.
-
B.
lessSevereIn
chosen
Indicates that one condition, event, or factor has a lower level of severity than another within a specified context.
-
C.
hydrationSupport
Indicates that one entity provides or enhances the hydration of another entity, helping to maintain or improve its water balance.
-
D.
canDryOut
Indicates that one entity has the ability or tendency to cause another entity to lose moisture and become dry.
-
E.
typicalDegree
Indicates the usual or characteristic level, intensity, or extent to which something holds or applies in a given context.
- 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.