Triple
T17714618
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Discaria articulata |
E442162
|
entity |
| Predicate | nitrogenFixationSymbiont |
P4281
|
FINISHED |
| Object | Frankia bacteria |
—
|
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: Frankia bacteria | Statement: [Discaria articulata, nitrogenFixationSymbiont, Frankia bacteria]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nitrogenFixationSymbiont Context triple: [Discaria articulata, nitrogenFixationSymbiont, Frankia bacteria]
-
A.
symbiontType
Indicates the specific kind or category of symbiotic relationship that exists between associated organisms.
-
B.
containsSymbioticAssociationsWith
Indicates that one entity includes or encompasses another entity with which it maintains a symbiotic (mutually dependent or beneficial) biological relationship.
-
C.
biota
Indicates the presence or composition of living organisms (flora, fauna, or other life forms) associated with a given entity or environment.
-
D.
nutrientUptake
Indicates the process by which an entity absorbs or takes in nutrients from its surrounding environment.
-
E.
fixesNitrogen
chosen
Indicates that the subject converts atmospheric nitrogen into biologically usable forms through nitrogen fixation.
- 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_69d8b9ec79688190b86bdcef85a7b3aa |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4747f217081909010f396caaf03be |
completed | April 19, 2026, 6:21 a.m. |
| PD | Predicate disambiguation | batch_69e3cde601d4819097903f471f1fe99a |
completed | April 18, 2026, 6:31 p.m. |
Created at: April 10, 2026, 10:06 a.m.