Triple
T8949325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cumberland Township, Pennsylvania |
E213303
|
entity |
| Predicate | hasPredominantLandUse |
P14072
|
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: [Cumberland Township, Pennsylvania, hasPredominantLandUse, agricultural]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPredominantLandUse Context triple: [Cumberland Township, Pennsylvania, hasPredominantLandUse, agricultural]
-
A.
majorLandUse
Indicates the primary way a given area of land is utilized or designated (e.g., residential, commercial, agricultural).
-
B.
primaryLandUse
chosen
Indicates the main or dominant way in which a given piece of land is utilized or designated (e.g., residential, agricultural, commercial).
-
C.
hasLandUseCharacter
Indicates that one entity possesses or is associated with a particular type or pattern of land use.
-
D.
landUseIncludes
Indicates that a specified land area contains or permits the specified type(s) of land use within its boundaries.
-
E.
hasLandUsePressure
Indicates that an area or entity is subject to demands or stresses from human or other uses of land that may affect its condition or availability.
- 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_69ca839843408190a39069a029a89f15 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc670b5f50819080f1c73992fe5281 |
completed | April 1, 2026, 12:30 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed5267c8190a43feb2a2f3df1ec |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 6:59 p.m.