Triple
T7848272
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mill Creek (Kansas) |
E181975
|
entity |
| Predicate | landUseInWatershed |
P25275
|
FINISHED |
| Object | agricultural |
—
|
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: agricultural | Statement: [Mill Creek (Kansas), landUseInWatershed, agricultural]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: landUseInWatershed Context triple: [Mill Creek (Kansas), landUseInWatershed, agricultural]
-
A.
hasWatershedUse
chosen
Indicates that a particular type of use, activity, or function is associated with or applied to a watershed.
-
B.
hasFloodplainUse
Indicates that a floodplain area is being used or designated for a particular purpose or activity.
-
C.
landUseIncludes
Indicates that a specified land area contains or permits the specified type(s) of land use within its boundaries.
-
D.
majorLandUse
Indicates the primary way a given area of land is utilized or designated (e.g., residential, commercial, agricultural).
-
E.
watershedType
Indicates the classification or category of a watershed associated with an entity (e.g., by hydrologic, ecological, or management type).
- 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_69ca82869ee08190b8f9040dbc2c0467 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb18e7f5988190808ae4dcfbc06991 |
completed | March 31, 2026, 12:44 a.m. |
| PD | Predicate disambiguation | batch_69cae92180f88190ae3d44c3de7adc93 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:50 p.m.