Triple
T14223968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clyde River (Tasmania) |
E352568
|
entity |
| Predicate | hasPrimaryLandUseInCatchment |
P107197
|
FINISHED |
| Object | 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: agriculture | Statement: [Clyde River (Tasmania), hasPrimaryLandUseInCatchment, agriculture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryLandUseInCatchment Context triple: [Clyde River (Tasmania), hasPrimaryLandUseInCatchment, agriculture]
-
A.
hasWatershedUse
Indicates that a particular type of use, activity, or function is associated with or applied to a watershed.
-
B.
drainageBasinLandUse
chosen
Indicates how the land within a drainage basin is utilized or managed (e.g., for agriculture, urban development, or natural vegetation).
-
C.
hasFloodplainUse
Indicates that a floodplain area is being used or designated for a particular purpose or activity.
-
D.
hasLandUseCharacter
Indicates that one entity possesses or is associated with a particular type or pattern of land use.
-
E.
hasMajorTownInCatchment
Indicates that a catchment area includes at least one major town within its geographic or service coverage.
- 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_69d8278a06e481908b5d6af0a8afe737 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6227c288819081473ce44f9f0934 |
completed | April 14, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69de05bcd7d48190a4848d9320404aa6 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:06 a.m.