Triple
T15561790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prairie County, Arkansas |
E371016
|
entity |
| Predicate | hasPredominantLandscape |
P9701
|
FINISHED |
| Object | prairie |
—
|
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: prairie | Statement: [Prairie County, Arkansas, hasPredominantLandscape, prairie]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPredominantLandscape Context triple: [Prairie County, Arkansas, hasPredominantLandscape, prairie]
-
A.
landscapeType
chosen
Indicates the kind or category of natural terrain or scenery that characterizes a place or area.
-
B.
hasLandscapeFeatures
Indicates that an entity possesses or includes specific landscape-related characteristics or elements.
-
C.
hasRuralLandscapeType
Indicates that an entity is associated with or characterized by a specific type of rural landscape.
-
D.
hasDiverseLandscape
Indicates that an entity possesses a variety of distinct physical or environmental features within its geographic area.
-
E.
hasMountainousTerrain
Indicates that a location or area possesses predominantly mountainous physical terrain or landscape features.
- 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_69d85cc6cf40819091f4a5facee1ebe6 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ddb4c0c81909b3f4c75c91f7f3f |
completed | April 16, 2026, 2:47 a.m. |
| PD | Predicate disambiguation | batch_69deda7e6e748190b29ccce23298afef |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:09 a.m.