Triple
T32197629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chaco woodland |
E822441
|
entity |
| Predicate | landUseConversionTo |
P81240
|
FINISHED |
| Object | soybean cultivation |
—
|
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: soybean cultivation | Statement: [Chaco woodland, landUseConversionTo, soybean cultivation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: landUseConversionTo Context triple: [Chaco woodland, landUseConversionTo, soybean cultivation]
-
A.
landUseChangeTo
chosen
Indicates a transition in how a piece of land is used, from its previous use to a new designated use.
-
B.
formerLandUse
Indicates the type of land use that characterized a location prior to its current or present use.
-
C.
landUseContext
Indicates the contextual setting or circumstances under which a particular piece of land is used or designated for a specific purpose.
-
D.
landUseIncludes
Indicates that a specified land area contains or permits the specified type(s) of land use within its boundaries.
-
E.
otherLandUse
Indicates that the land is used for purposes that do not fall into any of the primary or predefined land-use categories.
- 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_69f349093174819086e633c190a51aa8 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bb38af6c819082ad0dacc7acf54e |
completed | May 3, 2026, 3:04 a.m. |
| PD | Predicate disambiguation | batch_69f6b3aa892481908d29283a074e6722 |
completed | May 3, 2026, 2:32 a.m. |
Created at: May 1, 2026, 12:36 a.m.