Triple
T3872132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caenorhabditis elegans |
E92409
|
entity |
| Predicate | pathogenicToHumans |
P11983
|
FINISHED |
| Object | false |
—
|
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: false | Statement: [Caenorhabditis elegans, pathogenicToHumans, false]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pathogenicToHumans Context triple: [Caenorhabditis elegans, pathogenicToHumans, false]
-
A.
pathogenicityToHumans
chosen
Indicates that an entity has the capacity to cause disease or harmful health effects in humans.
-
B.
pathogenicity
Indicates that one entity has the capacity to cause disease or harmful pathological effects in another entity.
-
C.
pathogenType
Indicates the specific kind or category of pathogen associated with or responsible for an entity or condition.
-
D.
includesPathogensOf
Indicates that one entity contains or encompasses the pathogens that are associated with or originate from another entity.
-
E.
zoonoticPotential
Indicates the potential for a disease or pathogen to be transmitted from animals to humans.
- 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_69aed967448c819086c4b358d37b25aa |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee7574c408190893e70bf80514838 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:20 p.m.