Triple
T25929099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madagascar dry deciduous forests |
E653385
|
entity |
| Predicate | faunaExample |
P950
|
FINISHED |
| Object | Madagascar giant jumping rat |
—
|
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: Madagascar giant jumping rat | Statement: [Madagascar dry deciduous forests, faunaExample, Madagascar giant jumping rat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: faunaExample Context triple: [Madagascar dry deciduous forests, faunaExample, Madagascar giant jumping rat]
-
A.
fauna
chosen
Indicates that an entity is an animal or part of the animal life associated with a particular place or context.
-
B.
faunaNote
Indicates a note or annotation specifically about animals or wildlife associated with an entity or context.
-
C.
faunaDiversity
Indicates the variety and richness of animal species present within a given area or ecosystem.
-
D.
faunaCharacteristic
Indicates that an entity has a specific trait, feature, or quality related to animals or animal life.
-
E.
faunaOrigin
Indicates the place or source from which an animal species or population originates.
- 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_69f6041710b481909f9583a3bbe16475 |
completed | May 2, 2026, 2:03 p.m. |
| PD | Predicate disambiguation | batch_69f4a10480748190a2e67bd399fc435d |
completed | May 1, 2026, 12:48 p.m. |
Created at: April 22, 2026, 8:36 a.m.