Triple
T19715872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | neutral theory of population genetics |
E473474
|
entity |
| Predicate | providesModelFor |
P28233
|
FINISHED |
| Object | expected site frequency spectrum under neutrality |
—
|
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: expected site frequency spectrum under neutrality | Statement: [neutral theory of population genetics, providesModelFor, expected site frequency spectrum under neutrality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: providesModelFor Context triple: [neutral theory of population genetics, providesModelFor, expected site frequency spectrum under neutrality]
-
A.
introducedForModel
Indicates that one entity was created, proposed, or brought into use specifically for application within a particular model.
-
B.
possibleModel
Indicates that one entity can serve as a potential or candidate model or template for another entity.
-
C.
planningModelFor
Indicates that one entity serves as a planning model used to guide, simulate, or structure the planning activities related to another entity.
-
D.
isModelOf
chosen
Indicates that one entity serves as a representation or abstraction that captures the structure or behavior of another entity.
-
E.
producedModel
Indicates that one entity created, manufactured, or generated the other entity as a model or product.
- 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_69d8e516dd048190a0b6c93ea3e71f58 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6440cb47c81908124dfbd6f781d23 |
completed | April 20, 2026, 3:19 p.m. |
| PD | Predicate disambiguation | batch_69e530438c60819082364c7be3eef6f0 |
completed | April 19, 2026, 7:42 p.m. |
Created at: April 10, 2026, 1:46 p.m.