Triple
T240866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blood Cancer Discovery |
E4928
|
entity |
| Predicate | mainDiscipline |
P778
|
FINISHED |
| Object | hematology |
—
|
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: hematology | Statement: [Blood Cancer Discovery, mainDiscipline, hematology]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainDiscipline Context triple: [Blood Cancer Discovery, mainDiscipline, hematology]
-
A.
subDisciplineOf
Indicates that one discipline is a more specialized or narrower field within another, broader discipline.
-
B.
associatedWithDiscipline
Indicates that an entity has a relevant connection or involvement with a particular academic, professional, or thematic discipline.
-
C.
hasSubdiscipline
Indicates that one discipline includes another, more specialized field of study as a subordinate branch.
-
D.
academicFocus
chosen
Indicates the primary field of study, discipline, or subject area that an entity concentrates on academically.
-
E.
supportsDiscipline
Indicates that one entity provides assistance, resources, or endorsement that helps sustain or advance a particular discipline.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25d35aa288190966b6e15af1525cb |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b60ad308190b12f119960a8bde7 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.