Triple
T6724951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wet Tropics–subtropical transition zone |
E153492
|
entity |
| Predicate | oftenStudiedIn |
P770
|
FINISHED |
| Object | biogeography |
—
|
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: biogeography | Statement: [Wet Tropics–subtropical transition zone, oftenStudiedIn, biogeography]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenStudiedIn Context triple: [Wet Tropics–subtropical transition zone, oftenStudiedIn, biogeography]
-
A.
widelyStudiedIn
Indicates that something has been extensively researched, analyzed, or examined within a particular field, domain, or context.
-
B.
isStudiedIn
chosen
Indicates that a subject (such as a topic, field, or phenomenon) is examined, researched, or learned about within a particular context, environment, or discipline.
-
C.
studiedBy
Indicates that a subject (such as a field, topic, or object) is examined, researched, or learned by an agent (such as a person or group).
-
D.
stateStudied
Indicates that a person has studied or received education in a particular state.
-
E.
canBeStudiedAs
Indicates that something is suitable or appropriate to be examined, analyzed, or researched as a subject of study.
- 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_69c6880afb988190ad88011b48ecfcba |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d354177481908ab3cf5437c095e2 |
completed | March 27, 2026, 6:58 p.m. |
| PD | Predicate disambiguation | batch_69c6d08e8a2c8190ae4e8d8c039be7ce |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:08 p.m.