Triple
T16699623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | canton of Algrange |
E405809
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Russange |
E825003
|
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: Russange | Statement: [canton of Algrange, contains, Russange]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Russange Context triple: [canton of Algrange, contains, Russange]
-
A.
Russange
chosen
Russange is a small commune in northeastern France’s Grand Est region, near the borders with Luxembourg and Belgium.
-
B.
Rodange
Rodange is a town in southwestern Luxembourg known as an important railway junction near the Belgian and French borders.
-
C.
Rasoun
Rasoun is a small town in northern Jordan located within the hilly, forested region of Ajloun Governorate.
-
D.
Rumelange
Rumelange is a small town and commune in southwestern Luxembourg known for its historic iron-ore mining and the National Mining Museum.
-
E.
Roure
Roure is a small mountain commune in southeastern France, located in the Alpes-Maritimes department within the Provence-Alpes-Côte d’Azur 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_69d8838db21081909589220fd71440a4 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e383300d108190911e3cba8e07f2dd |
completed | April 18, 2026, 1:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00919ee61c81909928dd26270e9614 |
completed | May 10, 2026, 2:09 p.m. |
Created at: April 10, 2026, 5:19 a.m.