Triple
T29948872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hyphomicrobiales |
E760715
|
entity |
| Predicate | fixesNitrogenFor |
P4281
|
FINISHED |
| Object | legume root nodules |
—
|
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: legume root nodules | Statement: [Hyphomicrobiales, fixesNitrogenFor, legume root nodules]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fixesNitrogenFor Context triple: [Hyphomicrobiales, fixesNitrogenFor, legume root nodules]
-
A.
fixesNitrogen
chosen
Indicates that the subject converts atmospheric nitrogen into biologically usable forms through nitrogen fixation.
-
B.
hasNitrogenToPhosphorusRatio
Indicates that there is a specific quantitative relationship between the amount of nitrogen and the amount of phosphorus associated with an entity.
-
C.
fractionOfAtmosphericNitrogen
Indicates the proportion of atmospheric nitrogen that is attributed to, contained in, or associated with a given entity or context.
-
D.
isTypicallyNeutralizedWith
Indicates that something is commonly counteracted, rendered harmless, or balanced by another specified thing.
-
E.
hasCarbonToNitrogenRatio
Indicates the proportional relationship between the amount of carbon and the amount of nitrogen present in or associated with an 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_69f2246562b881909d57622f4086d43d |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6780dd5d08190b1ef4e49405a5419 |
completed | May 2, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69f66ec8298c8190b41fe9d182c05676 |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 29, 2026, 6:25 p.m.