Triple
T29905002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ras Initiative |
E759510
|
entity |
| Predicate | studiesGene |
P94165
|
FINISHED |
| Object | KRAS |
—
|
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: KRAS | Statement: [Ras Initiative, studiesGene, KRAS]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: studiesGene Context triple: [Ras Initiative, studiesGene, KRAS]
-
A.
geneticStudySubject
chosen
Indicates that an entity is the subject or focus of a genetic study or genetic analysis.
-
B.
targetsGene
Indicates that one entity is directed toward, acts upon, or is intended to affect a specific gene.
-
C.
studiesTrait
Indicates that one entity conducts research or examination focused on a particular trait or characteristic of another entity.
-
D.
geneticAssociation
Indicates that there is a statistically supported relationship between a genetic factor (e.g., variant, gene) and a particular trait, condition, or phenotype.
-
E.
alsoStudies
Indicates that an entity engages in studying an additional subject or field alongside another already being studied.
- 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_69f224600590819085e148a01c056ef6 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6775489c8819082f3ac9e756b6d92 |
completed | May 2, 2026, 10:14 p.m. |
| PD | Predicate disambiguation | batch_69f66ec8298c8190b41fe9d182c05676 |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 29, 2026, 6:08 p.m.