Triple
T36600391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CLEOPATRA trial |
E902898
|
entity |
| Predicate | diseaseStudied |
P65953
|
FINISHED |
| Object | HER2-positive metastatic breast 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: HER2-positive metastatic breast cancer | Statement: [CLEOPATRA trial, diseaseStudied, HER2-positive metastatic breast cancer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: diseaseStudied Context triple: [CLEOPATRA trial, diseaseStudied, HER2-positive metastatic breast cancer]
-
A.
hasTargetDisease
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.
conditionStudied
chosen
Indicates that a particular condition (e.g., disease, state, or circumstance) is the focus of study or investigation in a given context.
-
C.
diseaseType
Indicates that one entity is classified as a specific type or category of disease in relation to another entity.
-
D.
diseaseName
Indicates that the associated value specifies the name or designation of a particular disease.
-
E.
diseaseDepicted
Indicates that a visual representation (such as an image or illustration) shows or portrays a particular disease.
- 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_69f76e66b7b88190848f7a3e1188915f |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c371931c8190afb1d4dd5157f92c |
completed | May 3, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69f7c1baf25c8190a78dd54a400d2c50 |
completed | May 3, 2026, 9:44 p.m. |
Created at: May 3, 2026, 4:11 p.m.