Triple
T8525875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hodgeman County, Kansas |
E201814
|
entity |
| Predicate | ruralCharacteristic |
P47416
|
FINISHED |
| Object | low population density |
—
|
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: low population density | Statement: [Hodgeman County, Kansas, ruralCharacteristic, low population density]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ruralCharacteristic Context triple: [Hodgeman County, Kansas, ruralCharacteristic, low population density]
-
A.
semiRuralCharacter
Indicates that a place or area has characteristics intermediate between rural and urban, combining elements of both environments.
-
B.
isRural
Indicates that something is located in, characteristic of, or associated with a countryside or non-urban area.
-
C.
hasRuralArea
Indicates that an entity includes, is associated with, or contains a countryside or sparsely populated geographic area.
-
D.
isPredominantlyRural
chosen
Indicates that a place or region is characterized mainly by rural features, such as low population density and extensive non-urban land use.
-
E.
farmingCharacteristics
Indicates the specific methods, practices, or attributes that characterize how farming is conducted in relation to an entity.
- 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_69ca83228b24819085d22e7dc99f5d94 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe6463fe48190b6d3482212356be1 |
completed | March 31, 2026, 3:20 p.m. |
| PD | Predicate disambiguation | batch_69cbd10f64b4819080859057c19e58f0 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:16 p.m.