Triple
T16536276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lomela River |
E401698
|
entity |
| Predicate | hasLandcoverAround |
P85343
|
FINISHED |
| Object | tropical moist broadleaf forest |
—
|
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: tropical moist broadleaf forest | Statement: [Lomela River, hasLandcoverAround, tropical moist broadleaf forest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandcoverAround Context triple: [Lomela River, hasLandcoverAround, tropical moist broadleaf forest]
-
A.
hasNearbyLandscapeType
chosen
Indicates that one entity is located close to, or in the vicinity of, a particular type of landscape.
-
B.
hasNearbyLandUse
Indicates that one land area is located close to another area characterized by a specific type of land use.
-
C.
hasLandCoverage
Indicates that a specified area or region is covered or occupied by a particular type of land surface or land use.
-
D.
hasNearbyPublicLand
Indicates that one entity is located close to an area of public land, such as parks, reserves, or other publicly accessible open spaces.
-
E.
hasNearbyHabitats
Indicates that one entity has other habitats located close to it in geographic or spatial terms.
- 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_69d88384bc30819084229e7dcdc39a41 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e34558ec448190a6dcc15d62d1889c |
completed | April 18, 2026, 8:48 a.m. |
| PD | Predicate disambiguation | batch_69e2969fab208190ad64164d24748c45 |
completed | April 17, 2026, 8:22 p.m. |
Created at: April 10, 2026, 5:15 a.m.