Triple
T17597455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trichinellida |
E428609
|
entity |
| Predicate | infectionRouteInHumans |
P73776
|
FINISHED |
| Object | consumption of raw or undercooked pork |
—
|
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: consumption of raw or undercooked pork | Statement: [Trichinellida, infectionRouteInHumans, consumption of raw or undercooked pork]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: infectionRouteInHumans Context triple: [Trichinellida, infectionRouteInHumans, consumption of raw or undercooked pork]
-
A.
infectionMethod
chosen
Indicates the way or mechanism by which an infection is transmitted or established from a source to a host.
-
B.
pathogenicityToHumans
Indicates that an entity has the capacity to cause disease or harmful health effects in humans.
-
C.
transmissionBetweenHumans
Indicates that something (such as a disease, information, or influence) is passed directly from one human to another.
-
D.
infectionType
Indicates the specific category or nature of an infection associated with an entity or event.
-
E.
isPathogenOf
Indicates that one entity is a disease-causing agent (pathogen) that infects or causes illness in another entity.
- 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_69d889e1030481909950e140c63255b9 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e469ecfb108190a9e7a5b380f8ab93 |
completed | April 19, 2026, 5:36 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fff0348190b899a32da537eaca |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:51 a.m.