Triple
T498060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Basel–Mulhouse–Freiburg transport corridor |
E10338
|
entity |
| Predicate | includesCity |
P3207
|
FINISHED |
| Object | Basel |
E22322
|
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: Basel | Statement: [Basel–Mulhouse–Freiburg transport corridor, includesCity, Basel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Basel Context triple: [Basel–Mulhouse–Freiburg transport corridor, includesCity, Basel]
-
A.
Basel-Stadt
chosen
Basel-Stadt is a small, urban Swiss canton centered on the city of Basel, a major cultural and economic hub in northwestern Switzerland.
-
B.
Zurich
Zurich is the largest city in Switzerland, known as a global financial hub and cultural center situated on the shores of Lake Zurich.
-
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.
Biel/Bienne
Biel/Bienne is a bilingual (German-French) Swiss city in the canton of Bern, known for its watchmaking industry and location at the eastern end of Lake Biel.
-
E.
Lausanne
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.
- 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_69a2e847df8481909239ec08ccf1e376 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1183e988190bce70932a9678134 |
completed | Feb. 28, 2026, 1:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aca2c23ed481909453508bec526fd0 |
completed | March 7, 2026, 10:12 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.