Triple
T33778323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mau Forest |
E865582
|
entity |
| Predicate | isLargestIndigenousForestIn |
P177683
|
FINISHED |
| Object | Kenya |
—
|
NE NERFINISHED |
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: Kenya | Statement: [Mau Forest, isLargestIndigenousForestIn, Kenya]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isLargestIndigenousForestIn Context triple: [Mau Forest, isLargestIndigenousForestIn, Kenya]
-
A.
hasMajorRainforest
Indicates that one entity possesses or contains a large, significant rainforest within its area or domain.
-
B.
isLargestStateForestIn
Indicates that a state forest is the largest (by area) among all state forests located within a specified region or jurisdiction.
-
C.
forestArea
Indicates the extent or size of land covered by forest within a given area or region.
-
D.
largestProtectedAreaIn
Indicates that one entity is the largest protected area located within the boundaries of another entity (such as a region, country, or administrative unit).
-
E.
isLargestIslandIn
Indicates that one island is the largest (by area) among all islands within a specified geographic or political region.
- F. None of above. chosen
Provenance (4 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_69f3498df6f88190bf9647ea4e4a956e |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7009d39508190af7301f824615e88 |
completed | May 3, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69f6fc5740fc81909774a4f65201a3ff |
completed | May 3, 2026, 7:42 a.m. |
| PDg | Predicate description generation | batch_69f6ffb7554881908993d6d2ffbcf8f5 |
completed | May 3, 2026, 7:56 a.m. |
Created at: May 1, 2026, 1:45 a.m.