Triple
T21540560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colletotrichum |
E531471
|
entity |
| Predicate | infectionStrategy |
P66788
|
FINISHED |
| Object | hemibiotrophic |
—
|
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: hemibiotrophic | Statement: [Colletotrichum, infectionStrategy, hemibiotrophic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: infectionStrategy Context triple: [Colletotrichum, infectionStrategy, hemibiotrophic]
-
A.
infectionMethod
Indicates the way or mechanism by which an infection is transmitted or established from a source to a host.
-
B.
infectionType
chosen
Indicates the specific category or nature of an infection associated with an entity or event.
-
C.
infectionRequires
Indicates that the occurrence or establishment of an infection depends on the presence or fulfillment of a specified condition, factor, or prerequisite.
-
D.
infectionResult
Indicates that one entity causes or leads to a particular outcome, condition, or state as a result of an infection affecting another entity.
-
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.
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_69e0c45f17148190949c330ab9c27706 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee9d119e0c8190a207c0e8ae328a95 |
completed | April 26, 2026, 11:17 p.m. |
| PD | Predicate disambiguation | batch_69e6320766308190ba5dca2f7c826aa4 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:28 p.m.