Triple
T604479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vladimir Lenin |
E11564
|
entity |
| Predicate | residence |
P75
|
FINISHED |
| Object | Zurich, Switzerland |
E13407
|
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: Zurich, Switzerland | Statement: [Vladimir Lenin, residence, Zurich, Switzerland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zurich, Switzerland Context triple: [Vladimir Lenin, residence, Zurich, Switzerland]
-
A.
Bern, Switzerland
Bern, Switzerland is the de facto capital of Switzerland, known for its well-preserved medieval old town, political institutions, and cultural heritage.
-
B.
Zurich
chosen
Zurich is the largest city in Switzerland, known as a global financial hub and cultural center situated on the shores of Lake Zurich.
-
C.
Lausanne, Switzerland
Lausanne, Switzerland is a picturesque city on the shores of Lake Geneva known for its role as an Olympic capital and its vibrant cultural and academic life.
-
D.
Gland, Switzerland
Gland, Switzerland is a small town on the shores of Lake Geneva that is best known as a global hub for environmental and conservation organizations.
-
E.
Geneva
Geneva is a major Swiss city on Lake Geneva known for hosting numerous international organizations, including United Nations agencies and the Red Cross.
- 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_69a4932779b881908688590d59c71900 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49dc67b248190b0bb195553f03be8 |
completed | March 1, 2026, 8:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad089201a08190a84c7d8f32238297 |
completed | March 8, 2026, 5:26 a.m. |
Created at: March 1, 2026, 7:35 p.m.