Triple
T32195886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | chronic lymphocytic leukemia |
E822402
|
entity |
| Predicate | transformationSyndromeName |
P153793
|
FINISHED |
| Object | Richter transformation |
—
|
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: Richter transformation | Statement: [chronic lymphocytic leukemia, transformationSyndromeName, Richter transformation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transformationSyndromeName Context triple: [chronic lymphocytic leukemia, transformationSyndromeName, Richter transformation]
-
A.
conversionName
Indicates that one entity is the name or label assigned to a specific conversion event or conversion process associated with another entity.
-
B.
systematicName
Indicates that one entity is the formal, systematically constructed name assigned to the other entity according to a specific naming convention or standard.
-
C.
transformType
Indicates that one entity is converted or changed from its original form into another specified type or form.
-
D.
diseaseName
chosen
Indicates that the associated value specifies the name or designation of a particular disease.
-
E.
changesNameTo
Indicates that an entity alters its current name and adopts a new specified name.
- 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_69f3490819cc81909bae1f8ce99423c5 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fe8ddf70e48190a917eb9e8f7b6966 |
completed | May 9, 2026, 1:29 a.m. |
| PD | Predicate disambiguation | batch_69fe87ef94dc81909bb00ec8d6de9bcd |
completed | May 9, 2026, 1:03 a.m. |
Created at: May 1, 2026, 12:35 a.m.