Triple
T22413740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Organon |
E554058
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Organon & 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: Organon & Co. | Statement: [Organon, alsoKnownAs, Organon & Co.]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Organon & Co. Context triple: [Organon, alsoKnownAs, Organon & Co.]
-
A.
Organon & Co. (historical, later spun off)
chosen
Organon & Co. (historical, later spun off) was Merck & Co.’s women’s health and biosimilars-focused business unit that was separated into an independent pharmaceutical company.
-
B.
Gland Pharma
Gland Pharma is an Indian pharmaceutical company specializing in injectable formulations and contract manufacturing for global markets.
-
C.
Lonza
Lonza is a global Swiss-based life sciences company specializing in pharmaceutical, biotech, and nutrition products and services, particularly in contract development and manufacturing.
-
D.
Lonza
Lonza is a river in the Swiss canton of Valais that flows through the Lötschental valley before joining the Rhône.
-
E.
Hypera Pharma
Hypera Pharma is a major Brazilian pharmaceutical company known for producing a wide range of prescription and over-the-counter medicines and healthcare products.
- 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.