Triple
T24522466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cuc Phuong National Park |
E606569
|
entity |
| Predicate | faunaSpeciesCount |
P6211
|
FINISHED |
| Object | hundreds of vertebrate 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: hundreds of vertebrate species | Statement: [Cuc Phuong National Park, faunaSpeciesCount, hundreds of vertebrate species]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: faunaSpeciesCount Context triple: [Cuc Phuong National Park, faunaSpeciesCount, hundreds of vertebrate species]
-
A.
faunaDiversity
Indicates the variety and richness of animal species present within a given area or ecosystem.
-
B.
numberOfSpecies
chosen
Indicates the count of distinct species associated with a given entity or context.
-
C.
speciesNumber
Indicates the numerical identifier or count associated with a particular species in a given context.
-
D.
containsMostMammalSpecies
Indicates that one entity includes a greater number of mammal species within it than any comparable entity in the given context.
-
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_69e2c4c85778819085f5da9af3569ad5 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b0ca8081908d931aec560eae56 |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:25 a.m.