Triple
T16508392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anopheles |
E400989
|
entity |
| Predicate | numberOfMalariaVectorSpecies |
P6211
|
FINISHED |
| Object | about 30–40 important vector species |
—
|
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: about 30–40 important vector species | Statement: [Anopheles, numberOfMalariaVectorSpecies, about 30–40 important vector species]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMalariaVectorSpecies Context triple: [Anopheles, numberOfMalariaVectorSpecies, about 30–40 important vector species]
-
A.
numberOfSpecies
chosen
Indicates the count of distinct species associated with a given entity or context.
-
B.
speciesNumber
Indicates the numerical identifier or count associated with a particular species in a given context.
-
C.
diseaseVector
Indicates that one entity serves as a carrier or transmitter that spreads a disease-causing agent to another entity.
-
D.
hasEndemicSpecies
Indicates that a place or region contains species that are native to and found only within that specific geographic area.
-
E.
containsMostMammalSpecies
Indicates that one entity includes a greater number of mammal species within it than any comparable entity in the given context.
- 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_69d88381f6148190819958a038be990e |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e54331c8190b3c4f9de95cbbc5e |
completed | April 18, 2026, 7:10 a.m. |
| PD | Predicate disambiguation | batch_69e296902d6c8190884ddb612b8c5b36 |
completed | April 17, 2026, 8:22 p.m. |
Created at: April 10, 2026, 5:14 a.m.