Triple
T23650087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ciba-Geigy |
E584144
|
entity |
| Predicate | notableFieldOfResearch |
P934
|
FINISHED |
| Object | cardiovascular medicine |
—
|
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: cardiovascular medicine | Statement: [Ciba-Geigy, notableFieldOfResearch, cardiovascular medicine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableFieldOfResearch Context triple: [Ciba-Geigy, notableFieldOfResearch, cardiovascular medicine]
-
A.
notableContributionField
Indicates the field or domain in which an entity has made a significant or noteworthy contribution.
-
B.
hasResearchArea
chosen
Indicates that an entity (such as a person, project, or organization) is associated with or focused on a particular field or area of research.
-
C.
usesResearchSubject
Indicates that one entity employs or utilizes another entity as a research subject in a study or investigation.
-
D.
researchFocusSince
Indicates the point in time since which an entity has maintained a particular research focus or area of study.
-
E.
notableWorkConductedBy
Indicates that a particular notable work (such as a project, study, or creation) was carried out or executed by a specific agent or 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_69e248fefafc81909656921192f30e80 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b2885b408190a43dfed93309a4d6 |
completed | April 29, 2026, 7:26 a.m. |
| PD | Predicate disambiguation | batch_69f118d7903c8190bb590a71771e93af |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:49 p.m.