Triple
T22339580
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Halosphaeriaceae |
E552236
|
entity |
| Predicate | potentialApplication |
P106222
|
FINISHED |
| Object | biodegradation of marine wood waste |
—
|
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: biodegradation of marine wood waste | Statement: [Halosphaeriaceae, potentialApplication, biodegradation of marine wood waste]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: potentialApplication Context triple: [Halosphaeriaceae, potentialApplication, biodegradation of marine wood waste]
-
A.
aplicación
chosen
Indicates that one entity is the use or implementation of another entity for a specific purpose or function.
-
B.
relatedApplication
Indicates that one application has a defined connection or association with another application, such as dependency, complementarity, or functional linkage.
-
C.
applicationRequirement
Indicates that one entity specifies a condition or prerequisite that must be met for the use, approval, or execution of another entity or process.
-
D.
applicationRange
Indicates the scope or extent within which something (such as a rule, function, or process) is validly applied or operates.
-
E.
hasProfessionalApplication
Indicates that something is used or applied within a professional, occupational, or work-related context.
- 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_69e11e494eec81909c4d2d51f69499d9 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f157824f588190882bea9e61dd5a83 |
completed | April 29, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e7300c20088190a59e5bf9e70384f3 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:43 p.m.