Triple
T22413752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Organon |
E554058
|
entity |
| Predicate | spinOffFrom |
P7226
|
FINISHED |
| Object | Merck & Co. |
—
|
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 & Co. | Statement: [Organon, spinOffFrom, Merck & Co.]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Merck & Co. Context triple: [Organon, spinOffFrom, Merck & Co.]
-
A.
Merck & Co.
chosen
Merck & Co. is a major American pharmaceutical company known for developing and producing vaccines, oncology drugs, and other innovative medicines.
-
B.
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.
-
C.
Merck KGaA
Merck KGaA is a German multinational science and technology company specializing in healthcare, life science, and electronics.
-
D.
Pharmaceutical Research and Manufacturers of America
Pharmaceutical Research and Manufacturers of America is a major U.S. trade association representing leading biopharmaceutical and drug research companies.
-
E.
Pfizer
Pfizer is a major American multinational pharmaceutical and biotechnology corporation known for developing a wide range of prescription medicines and vaccines, including one of the first widely used COVID-19 vaccines.
- 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_69e11e4e6ce8819085a1e06d886bf21c |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1594496348190ba25dc0193d092f2 |
completed | April 29, 2026, 1:05 a.m. |
Created at: April 16, 2026, 8:46 p.m.