Triple
T19157168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MSD |
E468954
|
entity |
| Predicate | distinguishedFrom |
P1612
|
FINISHED |
| Object | Merck KGaA |
—
|
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: Merck KGaA | Statement: [MSD, distinguishedFrom, Merck KGaA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Merck KGaA Context triple: [MSD, distinguishedFrom, Merck KGaA]
-
A.
Merck KGaA
chosen
Merck KGaA is a German multinational science and technology company specializing in healthcare, life science, and electronics.
-
B.
Boehringer Ingelheim
Boehringer Ingelheim is a major German research-driven pharmaceutical company known for developing prescription medicines, animal health products, and biopharmaceuticals worldwide.
-
C.
Merck & Co.
Merck & Co. is a major American pharmaceutical company known for developing and producing vaccines, oncology drugs, and other innovative medicines.
-
D.
Schering
Schering is a German surname most notably associated with Ernst Schering, a 19th-century pharmacist and founder of the pharmaceutical company Schering AG.
-
E.
Bristol Myers Squibb
Bristol Myers Squibb is a global biopharmaceutical company known for developing and manufacturing innovative medicines in areas such as oncology, immunology, and cardiovascular disease.
- 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_69d8dd084ff48190ac0f8c46ee722629 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5eeb9cf9081908b17073755e83554 |
completed | April 20, 2026, 9:15 a.m. |
Created at: April 10, 2026, 12:06 p.m.