Triple
T9718970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al Jazirah state |
E235412
|
entity |
| Predicate | agriculturalSystemType |
P36685
|
FINISHED |
| Object | irrigated agriculture |
—
|
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: irrigated agriculture | Statement: [Al Jazirah state, agriculturalSystemType, irrigated agriculture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: agriculturalSystemType Context triple: [Al Jazirah state, agriculturalSystemType, irrigated agriculture]
-
A.
farmSystemOf
chosen
Indicates that one entity is the agricultural or farming system to which another entity belongs or with which it is associated.
-
B.
agriculturalPractice
Indicates a relationship where an entity engages in, applies, or is associated with a specific method or technique of agriculture or farming.
-
C.
farmingStructure
Indicates that one entity is a structure or facility used for farming-related activities in relation to another entity.
-
D.
hasAgriculturalCharacter
Indicates that something possesses qualities, features, or uses typical of agriculture or farming activities.
-
E.
agricultureUse
Indicates that something is used for, involved in, or designated for agricultural activities or purposes.
- 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_69ca84d0123c819096f9dc3b6abb0881 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9e4022c4819097455f14dd9b1a77 |
completed | April 1, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69cd03bfeca08190924fca43aaa9c10f |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:20 p.m.