Triple
T1345635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Murray Irrigation Area |
E28563
|
entity |
| Predicate | hasPolicyContext |
P11690
|
FINISHED |
| Object | subject to Murray–Darling Basin Plan |
—
|
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: subject to Murray–Darling Basin Plan | Statement: [Murray Irrigation Area, hasPolicyContext, subject to Murray–Darling Basin Plan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPolicyContext Context triple: [Murray Irrigation Area, hasPolicyContext, subject to Murray–Darling Basin Plan]
-
A.
hasPolicyArea
Indicates that an entity (such as a policy, program, or initiative) is associated with or pertains to a specific policy area or domain.
-
B.
hasPolicyBody
Indicates that an entity is associated with, or defined by, a specific policy document or policy text.
-
C.
policyContext
chosen
Indicates the situational or regulatory framework within which a policy is defined, interpreted, or applied.
-
D.
hasPolicyHistory
Indicates that an entity is associated with a record or sequence of past policies that have applied to it over time.
-
E.
hasPolicyGoal
Indicates that an entity is associated with, or aims to achieve, a specific policy objective or target.
- 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_69a49854eb3481908c7d56b2e449a290 |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c23e84188190b0395c57dd45b62a |
completed | March 1, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69a4bef5857c81909ae984feb85a26ca |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:56 p.m.