Triple
T2504128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mycobacterium tuberculosis |
E52537
|
entity |
| Predicate | diseaseInHumans |
P11983
|
FINISHED |
| Object | pulmonary tuberculosis |
—
|
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: pulmonary tuberculosis | Statement: [Mycobacterium tuberculosis, diseaseInHumans, pulmonary tuberculosis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: diseaseInHumans Context triple: [Mycobacterium tuberculosis, diseaseInHumans, pulmonary tuberculosis]
-
A.
diseaseType
Indicates that one entity is classified as a specific type or category of disease in relation to another entity.
-
B.
pathogenicityToHumans
chosen
Indicates that an entity has the capacity to cause disease or harmful health effects in humans.
-
C.
hasTargetDisease
Indicates that an entity (such as a treatment, study, or intervention) is directed toward, intended to affect, or primarily concerned with a specified disease.
-
D.
featuresDisease
Indicates that an entity exhibits, presents, or is characterized by a particular disease.
-
E.
diagnosedWith
Indicates that a subject has been identified, typically by a medical professional, as having a particular disease or medical condition.
- 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_69ab4957b3a88190adf968ae0c1b931c |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd1cd2db0819087d21ec49ffd9585 |
completed | March 7, 2026, 7:20 a.m. |
| PD | Predicate disambiguation | batch_69abd0bba5348190bb4637d3165cb339 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:46 p.m.