Triple
T37450301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coxiella |
E930654
|
entity |
| Predicate | diseaseCausedBySpecies |
P70352
|
FINISHED |
| Object | Q fever |
—
|
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: Q fever | Statement: [Coxiella, diseaseCausedBySpecies, Q fever]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: diseaseCausedBySpecies Context triple: [Coxiella, diseaseCausedBySpecies, Q fever]
-
A.
causesDiseaseType
Indicates that one entity is responsible for causing a specific type or category of disease in another entity.
-
B.
diseaseVectorGenus
Indicates that one entity is the biological genus of organisms that serve as vectors transmitting the disease associated with the other entity.
-
C.
zoonosisType
Indicates that a disease is transmitted from animals to humans, specifying the type or category of this animal-to-human transmission.
-
D.
diseaseVector
Indicates that one entity serves as a carrier or transmitter that spreads a disease-causing agent to another entity.
-
E.
includesSpeciesCausing
chosen
Indicates that one entity contains or encompasses species that are responsible for causing a particular effect, condition, or outcome in another 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_69f76ec0b9488190b7a4fae632bd1d2f |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba68077788190b311e027435fcf87 |
completed | May 6, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69fba34c65ac8190b298f0f00d1dcc0e |
completed | May 6, 2026, 8:23 p.m. |
Created at: May 3, 2026, 4:17 p.m.