Triple
T16699617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | canton of Algrange |
E405809
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Knutange |
E825001
|
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: Knutange | Statement: [canton of Algrange, contains, Knutange]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Knutange Context triple: [canton of Algrange, contains, Knutange]
-
A.
Knutange
chosen
Knutange is a small commune in northeastern France’s Grand Est region, historically shaped by the Lorraine industrial and mining basin.
-
B.
Lauterbourg
Lauterbourg is a small French town in the Alsace region near the German border, known for its cross-border role within the Upper Rhine area and its historic Rhine river setting.
-
C.
Barnacken
Barnacken is a hill in North Rhine-Westphalia, Germany, known as the highest elevation in the Teutoburg Forest range.
-
D.
Hagenborgh
Hagenborgh is a notable landmark building in the Dutch city of Almelo, recognized for its prominent role in the local urban landscape.
-
E.
Knodishall
Knodishall is a small rural village and civil parish in the county of Suffolk in eastern England.
- 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.