Triple
T19773197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LONN |
E474938
|
entity |
| Predicate | hasUnderlyingIssuer |
P37863
|
FINISHED |
| Object | Lonza Group AG |
—
|
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: Lonza Group AG | Statement: [LONN, hasUnderlyingIssuer, Lonza Group AG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lonza Group AG Context triple: [LONN, hasUnderlyingIssuer, Lonza Group AG]
-
A.
Lonza
chosen
Lonza is a global Swiss-based life sciences company specializing in pharmaceutical, biotech, and nutrition products and services, particularly in contract development and manufacturing.
-
B.
Lonza
Lonza is a river in the Swiss canton of Valais that flows through the Lötschental valley before joining the Rhône.
-
C.
Boehringer Ingelheim
Boehringer Ingelheim is a major German research-driven pharmaceutical company known for developing prescription medicines, animal health products, and biopharmaceuticals worldwide.
-
D.
Merck KGaA
Merck KGaA is a German multinational science and technology company specializing in healthcare, life science, and electronics.
-
E.
Novartis
Novartis is a global Swiss-based pharmaceutical company known for developing innovative medicines across a wide range of therapeutic areas.
- 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_69d8e51a43a08190956bc6df13c91a77 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6535e450c8190a2628245ae0d0bd3 |
completed | April 20, 2026, 4:25 p.m. |
Created at: April 10, 2026, 1:48 p.m.