Triple
T404519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Republic of the Congo |
E9354
|
entity |
| Predicate | hasMajorBiome |
P952
|
FINISHED |
| Object | tropical rainforest |
—
|
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 rainforest | Statement: [Republic of the Congo, hasMajorBiome, tropical rainforest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMajorBiome Context triple: [Republic of the Congo, hasMajorBiome, tropical rainforest]
-
A.
biome
chosen
Indicates the type of ecological environment or habitat in which an entity naturally exists or is situated.
-
B.
hasBiosphere
Indicates that an entity possesses or supports a biosphere, i.e., a region where living organisms and ecological processes exist.
-
C.
hasMajorRainforest
Indicates that one entity possesses or contains a large, significant rainforest within its area or domain.
-
D.
hasMajorLake
Indicates that a geographic region or area contains at least one significant lake within its boundaries.
-
E.
hasMajorDesert
Indicates that a region or country contains at least one large, significant desert within its territory.
- 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_69a2e8004cb88190b92ed1add6abf41a |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2eca37fe881909802126952dfdd59 |
completed | Feb. 28, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69a2e97066e8819083cc1b3a421b9650 |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.