Triple
T21324606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lausanne–Villeneuve railway line |
E525715
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Epesses |
E261419
|
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: Epesses | Statement: [Lausanne–Villeneuve railway line, serves, Epesses]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Epesses Context triple: [Lausanne–Villeneuve railway line, serves, Epesses]
-
A.
Epesses
chosen
Epesses is a picturesque wine-growing village in Switzerland’s Lavaux region, renowned for its terraced vineyards overlooking Lake Geneva.
-
B.
Eppegem
Eppegem is a village in the Flemish Brabant province of Belgium, known as one of the constituent towns of the municipality of Zemst.
-
C.
Sospel
Sospel is a historic village in southeastern France near the Italian border, known for its medieval architecture and picturesque setting in the Maritime Alps.
-
D.
Effretikon
Effretikon is a town in the municipality of Illnau-Effretikon in the canton of Zurich, Switzerland, known as a regional transport hub and residential community.
-
E.
Étoges
Étoges is a small commune in northeastern France, known for its historic château and its location in the Champagne wine-producing region.
- 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_69e0b51ad810819098c12392c8e55f6c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e77ed7732c8190a0e7aec6e7cbcef2 |
completed | April 21, 2026, 1:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a099ee66f408190962424b053ad54cc |
completed | May 17, 2026, 10:56 a.m. |
Created at: April 16, 2026, 4:40 p.m.