Triple
T38021907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mycobacterium suricattae |
E948657
|
entity |
| Predicate | causesLesionsIn |
P6647
|
FINISHED |
| Object | lungs of meerkats |
—
|
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: lungs of meerkats | Statement: [Mycobacterium suricattae, causesLesionsIn, lungs of meerkats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causesLesionsIn Context triple: [Mycobacterium suricattae, causesLesionsIn, lungs of meerkats]
-
A.
lesionType
Indicates the specific kind or category of lesion involved in the relationship or event.
-
B.
causesDiseaseType
Indicates that one entity is responsible for causing a specific type or category of disease in another entity.
-
C.
lesionAssociatedWithSymptom
Indicates that a particular lesion is linked to, or occurs together with, a specific symptom.
-
D.
infectsTissue
chosen
Indicates that one entity (typically a pathogen or agent) invades and establishes itself within the tissue of another entity.
-
E.
causesDiseaseInPlants
Indicates that one entity is responsible for causing a disease or pathological condition in plants.
- 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_69f76efc10448190aff5fb566b98f952 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fd7b0503a08190ba07338365b6fcc9 |
completed | May 8, 2026, 5:56 a.m. |
| PD | Predicate disambiguation | batch_69fd7a9733dc81909199f453c0cc2bc1 |
completed | May 8, 2026, 5:54 a.m. |
Created at: May 3, 2026, 4:20 p.m.