Triple
T13754707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Degania Alef |
E330444
|
entity |
| Predicate | hasAgriculturalBranch |
P40002
|
FINISHED |
| Object | field crops |
—
|
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: field crops | Statement: [Degania Alef, hasAgriculturalBranch, field crops]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAgriculturalBranch Context triple: [Degania Alef, hasAgriculturalBranch, field crops]
-
A.
hasAgriculturalProduction
Indicates that an entity engages in or is characterized by the production of agricultural goods such as crops or livestock.
-
B.
hasAgriculturalAssociation
Indicates that there exists a formal or recognized connection between an entity and an agricultural organization, group, or activity.
-
C.
hasAgriculturalCharacter
chosen
Indicates that something possesses qualities, features, or uses typical of agriculture or farming activities.
-
D.
representsAgriculture
Indicates that one entity serves as an example, instance, or embodiment of agriculture in relation to another entity.
-
E.
haveAgriculturalTrade
Indicates that there is an ongoing exchange of agricultural goods or services between the related entities.
- 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_69d81c573f288190aa2403d484fa3d49 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02179c948190a652cc8c586e418f |
completed | April 14, 2026, 9 a.m. |
| PD | Predicate disambiguation | batch_69dbbe950b148190ba0df8a749269ec6 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 10:09 p.m.