Triple
T1232786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Romandie |
E26480
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Lausanne |
E74605
|
NE FINISHED |
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: Lausanne | Statement: [Romandie, hasMajorCity, Lausanne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lausanne Context triple: [Romandie, hasMajorCity, Lausanne]
-
A.
Lausanne
chosen
Lausanne is a major Swiss city on the shores of Lake Geneva, known for hosting the International Olympic Committee and its vibrant cultural and academic institutions.
-
B.
Neuchâtel
Neuchâtel is a French-speaking canton in western Switzerland known for its lakeside capital, watchmaking industry, and historic architecture.
-
C.
Geneva
Geneva is a major Swiss city on Lake Geneva known for hosting numerous international organizations, including United Nations agencies and the Red Cross.
-
D.
Nyon
Nyon is a Swiss town on the shores of Lake Geneva that serves as the administrative home of several major sports organizations, including UEFA.
-
E.
Montreux
Montreux is a picturesque resort town in southwestern Switzerland, renowned for its lakeside promenade, mild microclimate, and the annual Montreux Jazz Festival.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a4948571c88190a9191e451e6035fd |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be5b40208190b115a6a344402caf |
completed | March 1, 2026, 10:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b432e294348190af62caa0d5fce580 |
completed | March 13, 2026, 3:53 p.m. |
Created at: March 1, 2026, 7:47 p.m.