Triple
T12763925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Legionella |
E305069
|
entity |
| Predicate | virulenceMechanism |
P68675
|
FINISHED |
| Object | type IV secretion system |
—
|
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: type IV secretion system | Statement: [Legionella, virulenceMechanism, type IV secretion system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: virulenceMechanism Context triple: [Legionella, virulenceMechanism, type IV secretion system]
-
A.
virulenceFactor
Indicates that an entity contributes to the ability of a pathogen to infect, damage, or evade the defenses of its host.
-
B.
virulence
Indicates the degree to which a pathogen or harmful agent is capable of causing damage, disease, or severe effects in its host.
-
C.
pathogenicMechanism
chosen
Indicates the specific biological process or mechanism through which an agent causes disease or pathological effects in a host.
-
D.
pathogenicity
Indicates that one entity has the capacity to cause disease or harmful pathological effects in another entity.
-
E.
pathogenType
Indicates the specific kind or category of pathogen associated with or responsible for an entity or 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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d8f9f588190bffdea878856204b |
completed | April 10, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69d96409739881909174ba005a986cb5 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:28 p.m.