Triple
T1759220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monera |
E38616
|
entity |
| Predicate | includesPathogensOf |
P31424
|
FINISHED |
| Object | humans |
—
|
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: humans | Statement: [Monera, includesPathogensOf, humans]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesPathogensOf Context triple: [Monera, includesPathogensOf, humans]
-
A.
pathogenType
Indicates the specific kind or category of pathogen associated with or responsible for an entity or condition.
-
B.
pathogenicityToHumans
Indicates that an entity has the capacity to cause disease or harmful health effects in humans.
-
C.
pathogenGenus
Indicates that one entity is a pathogen belonging to, or classified under, the specified genus.
-
D.
isReservoirOf
Indicates that one entity serves as a storage source or container holding a particular substance, resource, or quantity for another entity or purpose.
-
E.
infectsTissue
Indicates that one entity (typically a pathogen or agent) invades and establishes itself within the tissue of another entity.
- F. None of above. chosen
Provenance (4 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_69a8862d562481908d7025a1c1f67c0d |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab173936b4819097332ee185996bbd |
completed | March 6, 2026, 6:04 p.m. |
| PD | Predicate disambiguation | batch_69aa61c9e06c819085489e00cfe72153 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab173830a481908b67928f16f5d999 |
completed | March 6, 2026, 6:04 p.m. |
Created at: March 4, 2026, 7:31 p.m.