Triple
T19577073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montreux Oberland Bernois Railway |
E489884
|
entity |
| Predicate | hasDepot |
P2413
|
FINISHED |
| Object |
Chernex
Chernex is a village in the canton of Vaud, Switzerland, known as a stop and maintenance hub on the Montreux Oberland Bernois Railway.
|
E1383250
|
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: Chernex | Statement: [Montreux Oberland Bernois Railway, hasDepot, Chernex]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chernex Context triple: [Montreux Oberland Bernois Railway, hasDepot, Chernex]
-
A.
Brillo
Brillo is a lightweight, Android-based operating system developed by Google for powering and managing Internet of Things (IoT) devices.
-
B.
Drano
Drano is a widely used household chemical product designed to clear clogged drains and pipes.
-
C.
Harpic
Harpic is a widely used brand of toilet and bathroom cleaning products known for its powerful disinfecting and stain-removal formulations.
-
D.
Tipp-Ex
Tipp-Ex is a well-known brand of correction fluid and related correction products commonly used to cover typing or writing errors on paper.
-
E.
Skoal
Skoal is a leading U.S. smokeless tobacco brand best known for its moist snuff products.
- 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: Chernex Triple: [Montreux Oberland Bernois Railway, hasDepot, Chernex]
Generated description
Chernex is a village in the canton of Vaud, Switzerland, known as a stop and maintenance hub on the Montreux Oberland Bernois Railway.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Chernex Target entity description: Chernex is a village in the canton of Vaud, Switzerland, known as a stop and maintenance hub on the Montreux Oberland Bernois Railway.
-
A.
Brillo
Brillo is a lightweight, Android-based operating system developed by Google for powering and managing Internet of Things (IoT) devices.
-
B.
Drano
Drano is a widely used household chemical product designed to clear clogged drains and pipes.
-
C.
Harpic
Harpic is a widely used brand of toilet and bathroom cleaning products known for its powerful disinfecting and stain-removal formulations.
-
D.
Tipp-Ex
Tipp-Ex is a well-known brand of correction fluid and related correction products commonly used to cover typing or writing errors on paper.
-
E.
Skoal
Skoal is a leading U.S. smokeless tobacco brand best known for its moist snuff products.
- 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_69d8e8dd9374819098e36349b3211663 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e64025d5d081909dbb0c079d366006 |
completed | April 20, 2026, 3:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a075792581881909443cecc6a9212e4 |
completed | May 15, 2026, 5:27 p.m. |
| NEDg | Description generation | batch_6a0758be89108190adb2369750eb90ca |
completed | May 15, 2026, 5:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07599d4c988190a32a0aa9e561a61d |
completed | May 15, 2026, 5:36 p.m. |
Created at: April 10, 2026, 1:42 p.m.