Triple
T38561151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | tularemia |
E928077
|
entity |
| Predicate | mortalityWithoutTreatment |
P4715
|
FINISHED |
| Object | can be high in severe forms |
—
|
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: can be high in severe forms | Statement: [tularemia, mortalityWithoutTreatment, can be high in severe forms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mortalityWithoutTreatment Context triple: [tularemia, mortalityWithoutTreatment, can be high in severe forms]
-
A.
mortalityRate
chosen
Indicates the proportion of individuals in a defined population that die within a specified time period.
-
B.
deathWithoutIssue
Indicates that a person has died without leaving any surviving descendants or heirs.
-
C.
deathOutcome
Indicates that an event, condition, or action results in the death of the affected entity.
-
D.
mortalStatus
Indicates the state or condition of an entity with respect to being mortal, immortal, or otherwise subject to death.
-
E.
doesNotCure
Indicates that an action, treatment, or intervention fails to eliminate or resolve a condition, problem, or disease in the affected entity.
- 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_69f76eb8d1808190a588af29d8b266d6 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdaa36f90819093f8661969990c7d |
completed | May 7, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69fcd8fefc588190b063d7ea1ec87b07 |
completed | May 7, 2026, 6:25 p.m. |
Created at: May 3, 2026, 4:32 p.m.