Triple
T19157021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Merck |
E468951
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | George Merck |
—
|
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: George Merck | Statement: [George Merck, name, George Merck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: George Merck Context triple: [George Merck, name, George Merck]
-
A.
George Merck
chosen
George Merck was an American pharmaceutical executive best known for leading and expanding Merck & Co. into a major global drug company in the early 20th century.
-
B.
Ernst Schering
Ernst Schering was a German mathematician and physicist known for his work in geodesy and potential theory in the 19th century.
-
C.
Fritz Hoffmann-La Roche
Fritz Hoffmann-La Roche was a Swiss entrepreneur and industrialist who founded the global healthcare and pharmaceutical company Roche in the late 19th century.
-
D.
Anselm Franz von Ingelheim
Anselm Franz von Ingelheim was a 17th-century German archbishop and statesman who served as Archbishop-Elector of Mainz, making him one of the most influential ecclesiastical princes in the Holy Roman Empire.
-
E.
G.D. Searle
G.D. Searle is a pharmaceutical company best known for developing the artificial sweetener aspartame and for its role in pioneering modern drug research before becoming part of larger industry conglomerates.
- 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.