Triple
T31535776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mucuna pruriens |
E804595
|
entity |
| Predicate | agriculturalBenefit |
P107722
|
FINISHED |
| Object | nitrogen fixation |
—
|
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: nitrogen fixation | Statement: [Mucuna pruriens, agriculturalBenefit, nitrogen fixation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: agriculturalBenefit Context triple: [Mucuna pruriens, agriculturalBenefit, nitrogen fixation]
-
A.
agriculturalImplication
chosen
Indicates a relationship where one factor, event, or condition has consequences, effects, or relevance specifically within an agricultural context.
-
B.
agricultureUse
Indicates that something is used for, involved in, or designated for agricultural activities or purposes.
-
C.
agriculturalImpact
Indicates the effect that an action, condition, or entity has on agricultural systems, productivity, or practices.
-
D.
agriculturalFocus
Indicates that an entity is primarily concerned with, oriented toward, or specializing in agriculture or farming-related activities.
-
E.
agriculturalProductivity
Indicates the level or efficiency of agricultural output produced relative to the resources or inputs used.
- 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_69f348d03ef88190a2b73d7b94b9e02d |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a8055f8081908f635fe04654b5fe |
completed | May 3, 2026, 1:42 a.m. |
| PD | Predicate disambiguation | batch_69f6a75656e081908739ed9e2f600e42 |
completed | May 3, 2026, 1:39 a.m. |
Created at: April 30, 2026, 10:03 p.m.