Triple
T37449962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francisella |
E930647
|
entity |
| Predicate | diseaseCausedByNotableSpecies |
P153406
|
FINISHED |
| Object | tularemia |
—
|
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: tularemia | Statement: [Francisella, diseaseCausedByNotableSpecies, tularemia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: diseaseCausedByNotableSpecies Context triple: [Francisella, diseaseCausedByNotableSpecies, tularemia]
-
A.
causesDiseaseType
chosen
Indicates that one entity is responsible for causing a specific type or category of disease in another entity.
-
B.
notableSpecies
Indicates that the subject is known for, or significantly associated with, the specified species.
-
C.
speciesAssociatedWith
Indicates that there is a relevant connection or linkage between a species and another entity (such as a habitat, condition, or feature), without specifying the exact nature of that relationship.
-
D.
diseaseVector
Indicates that one entity serves as a carrier or transmitter that spreads a disease-causing agent to another entity.
-
E.
diseaseVectorGenus
Indicates that one entity is the biological genus of organisms that serve as vectors transmitting the disease associated with the other 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_69fb92efc5948190a040ba2028bab964 |
completed | May 6, 2026, 7:13 p.m. |
| PD | Predicate disambiguation | batch_69fb8d0b52588190bb29937a43b99b5e |
completed | May 6, 2026, 6:48 p.m. |
Created at: May 3, 2026, 4:17 p.m.