Triple
T11165349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yoshinori Ohsumi |
E264145
|
entity |
| Predicate | usesResearchOrganism |
P51389
|
FINISHED |
| Object | yeast |
—
|
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: yeast | Statement: [Yoshinori Ohsumi, usesResearchOrganism, yeast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesResearchOrganism Context triple: [Yoshinori Ohsumi, usesResearchOrganism, yeast]
-
A.
studiedOrganism
chosen
Indicates that an entity conducted study or research on a particular organism.
-
B.
isModelOrganism
Indicates that one organism is used as a representative experimental system for studying biological processes relevant to other organisms.
-
C.
targetOrganism
Indicates that an action, process, or effect is directed toward or intended to impact a particular organism.
-
D.
notableModelOrganism
Indicates that an organism is widely recognized and frequently used as a standard or reference model for scientific research or experimentation.
-
E.
containsModelOrganisms
Indicates that one entity includes or incorporates model organisms as part of its contents or composition.
- 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_69d6aa9ccddc8190868998c8b7beb060 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e887293081909830852000d533fa |
completed | April 9, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69d75cec26fc8190a5497d186306f935 |
completed | April 9, 2026, 8:01 a.m. |
Created at: April 8, 2026, 9:29 p.m.