Triple
T32804628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fabeae |
E838988
|
entity |
| Predicate | hasAgronomicRelevance |
P107722
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Fabeae, hasAgronomicRelevance, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAgronomicRelevance Context triple: [Fabeae, hasAgronomicRelevance, yes]
-
A.
agronomicTrait
Indicates a relationship where a trait is characterized specifically in terms of its relevance to agricultural growth, management, or productivity of plants or crops.
-
B.
hasCropSpecies
Indicates that a particular location, field, or agricultural system is associated with or used to cultivate a specified crop species.
-
C.
hasAgriculturalType
Indicates that an entity is associated with or classified by a specific type or category of agriculture.
-
D.
hasAgriculturalCharacter
Indicates that something possesses qualities, features, or uses typical of agriculture or farming activities.
-
E.
agriculturalImplication
chosen
Indicates a relationship where one factor, event, or condition has consequences, effects, or relevance specifically within an agricultural 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_69f3493d35208190b4351b4e85f2fa16 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6ce6d659881909ddcec1d2966e020 |
completed | May 3, 2026, 4:26 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1667a48190b42684f6ec22dae9 |
completed | May 3, 2026, 4:16 a.m. |
Created at: May 1, 2026, 1:15 a.m.