Triple
T4699665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MRC Protein Phosphorylation and Ubiquitylation Unit |
E104236
|
entity |
| Predicate | studiesDisease |
P20980
|
FINISHED |
| Object | cancer |
—
|
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: cancer | Statement: [MRC Protein Phosphorylation and Ubiquitylation Unit, studiesDisease, cancer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: studiesDisease Context triple: [MRC Protein Phosphorylation and Ubiquitylation Unit, studiesDisease, cancer]
-
A.
hasTargetDisease
chosen
Indicates that an entity (such as a treatment, study, or intervention) is directed toward, intended to affect, or primarily concerned with a specified disease.
-
B.
humanDisease
Indicates that the subject is a disease that affects humans.
-
C.
diseaseType
Indicates that one entity is classified as a specific type or category of disease in relation to another entity.
-
D.
riskFactorTypeStudied
Indicates that a particular type of risk factor is the subject of study or analysis in a given context.
-
E.
diseaseVector
Indicates that one entity serves as a carrier or transmitter that spreads a disease-causing agent to another entity.
- 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_69bd43e9b88481908582103dcadff3d9 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd650ad0f88190844bfcb46b3071c2 |
completed | March 20, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_69bd621ba7448190a53ab1e2897acf71 |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:17 p.m.