Triple
T26493720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daen Lao Range |
E669223
|
entity |
| Predicate | hasLandUseIssue |
P141795
|
FINISHED |
| Object | deforestation in some areas |
—
|
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: deforestation in some areas | Statement: [Daen Lao Range, hasLandUseIssue, deforestation in some areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandUseIssue Context triple: [Daen Lao Range, hasLandUseIssue, deforestation in some areas]
-
A.
landUseIssues
chosen
Indicates conflicts, problems, or concerns arising from how land is used, managed, or designated.
-
B.
hasLandUseCharacter
Indicates that one entity possesses or is associated with a particular type or pattern of land use.
-
C.
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.
-
D.
hasUrbanIssue
Indicates that an entity experiences, is affected by, or is associated with a specific problem or challenge related to urban environments or city life.
-
E.
landUseIncludes
Indicates that a specified land area contains or permits the specified type(s) of land use within its boundaries.
- 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_69eeb319007081909642b414b114b35a |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f7221dc9a88190bb8194fcc29c42bc |
completed | May 3, 2026, 10:23 a.m. |
| PD | Predicate disambiguation | batch_69f72153a9188190b02adc84e1be4af8 |
completed | May 3, 2026, 10:20 a.m. |
Created at: April 27, 2026, 1:06 a.m.