Triple
T18644846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Novo Nordisk |
E455777
|
entity |
| Predicate | majorProduct |
P7216
|
FINISHED |
| Object | Victoza |
—
|
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: Victoza | Statement: [Novo Nordisk, majorProduct, Victoza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Victoza Context triple: [Novo Nordisk, majorProduct, Victoza]
-
A.
Farxiga
Farxiga is a prescription SGLT2 inhibitor medication used primarily to treat type 2 diabetes and reduce the risk of cardiovascular and kidney complications.
-
B.
Mounjaro
Mounjaro is a prescription medication (tirzepatide) used primarily to improve blood sugar control in adults with type 2 diabetes and increasingly known for its weight-loss effects.
-
C.
Rinvoq
Rinvoq is a prescription JAK inhibitor medication used to treat various inflammatory and autoimmune conditions such as rheumatoid arthritis and atopic dermatitis.
-
D.
Trulicity
chosen
Trulicity is a prescription GLP-1 receptor agonist medication used to improve blood sugar control in adults with type 2 diabetes.
-
E.
Anpezan
Anpezan is a regional dialect of the Ladin language spoken in parts of the Dolomite area of northern Italy.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d38ea1e88190997e9b231190ba6f |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5500c36188190bfdd7aca73f3c006 |
completed | April 19, 2026, 9:58 p.m. |
Created at: April 10, 2026, 11:47 a.m.