Triple
T17421982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goppenstein |
E423638
|
entity |
| Predicate | locatedOnRiver |
P165
|
FINISHED |
| Object |
Lonza
Lonza is a river in the Swiss canton of Valais that flows through the Lötschental valley before joining the Rhône.
|
E1268225
|
NE FINISHED |
How this triple was built (4 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 | Statement: [Goppenstein, locatedOnRiver, Lonza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lonza Context triple: [Goppenstein, locatedOnRiver, Lonza]
-
A.
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.
-
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.
Novartis
Novartis is a global Swiss-based pharmaceutical company known for developing innovative medicines across a wide range of therapeutic areas.
-
D.
Ciba-Geigy
Ciba-Geigy was a major Swiss pharmaceutical and chemical company that became one of the predecessors of Novartis after its merger with Sandoz in 1996.
-
E.
Roche
Roche is a common surname of French origin borne by various notable individuals across fields such as architecture, politics, and the arts.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lonza Triple: [Goppenstein, locatedOnRiver, Lonza]
Generated description
Lonza is a river in the Swiss canton of Valais that flows through the Lötschental valley before joining the Rhône.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lonza Target entity description: Lonza is a river in the Swiss canton of Valais that flows through the Lötschental valley before joining the Rhône.
-
A.
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.
-
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.
Novartis
Novartis is a global Swiss-based pharmaceutical company known for developing innovative medicines across a wide range of therapeutic areas.
-
D.
Ciba-Geigy
Ciba-Geigy was a major Swiss pharmaceutical and chemical company that became one of the predecessors of Novartis after its merger with Sandoz in 1996.
-
E.
Roche
Roche is a common surname of French origin borne by various notable individuals across fields such as architecture, politics, and the arts.
- F. None of above. chosen
Provenance (5 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_69d889d7d27c819088486ce3f0627fa1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e44237f2cc819083ca0e7e00d828fb |
completed | April 19, 2026, 2:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01a8041f548190a076b10516ccfced |
completed | May 11, 2026, 9:57 a.m. |
| NEDg | Description generation | batch_6a01a8d7e05c8190aceb0795a430fee7 |
completed | May 11, 2026, 10 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01a943fdec8190a875c7eb56c742da |
completed | May 11, 2026, 10:02 a.m. |
Created at: April 10, 2026, 5:46 a.m.