Triple
T25929087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madagascar dry deciduous forests |
E653385
|
entity |
| Predicate | characteristicVegetation |
P953
|
FINISHED |
| Object | deciduous woodland |
—
|
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: deciduous woodland | Statement: [Madagascar dry deciduous forests, characteristicVegetation, deciduous woodland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characteristicVegetation Context triple: [Madagascar dry deciduous forests, characteristicVegetation, deciduous woodland]
-
A.
vegetationType
chosen
Indicates the specific kind or category of plant cover or flora that characterizes a given area or environment.
-
B.
forestCoverCharacteristic
Indicates a relationship where a forested area possesses a specific attribute or quality related to its tree or vegetation cover.
-
C.
vegetationStructure
Indicates the structural characteristics or arrangement of plant life in an area, such as its layering, density, or complexity.
-
D.
vegetationCoverage
Indicates the extent or proportion of an area that is covered by vegetation.
-
E.
vegetation
Indicates that an area or object is covered with, contains, or is characterized by plant life.
- 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_69e7ab3eb9b881909c1390690551f868 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6a28c7c148190bfc980aad9f678ca |
completed | May 3, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69f69fe1e3c88190830bb2e9f407357e |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 22, 2026, 8:36 a.m.