Triple
T1614997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walther Nernst |
E34696
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object |
Briesen
Briesen is a small town in present-day Germany best known as the birthplace of Nobel Prize–winning chemist Walther Nernst.
|
E220995
|
NE FINISHED |
How this triple was built (4 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: Briesen | Statement: [Walther Nernst, placeOfBirth, Briesen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Briesen Context triple: [Walther Nernst, placeOfBirth, Briesen]
-
A.
Günsberg
Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
-
B.
Böbing
Böbing is a small municipality in the Weilheim-Schongau district of Bavaria, Germany, known for its rural setting in the Alpine foothills.
-
C.
Rheydt
Rheydt is a district of the German city of Mönchengladbach in North Rhine-Westphalia, historically an independent town in the Rhineland.
-
D.
Biebrich
Biebrich is a district of Wiesbaden in the German state of Hesse, historically known as an independent town on the Rhine and the site of the Baroque Biebrich Palace.
-
E.
Radevormwald
Radevormwald is a small historic town in North Rhine-Westphalia, western Germany, known for its hilly Bergisches Land landscape and traditional textile and metalworking industries.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Briesen Triple: [Walther Nernst, placeOfBirth, Briesen]
Generated description
Briesen is a small town in present-day Germany best known as the birthplace of Nobel Prize–winning chemist Walther Nernst.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Briesen Target entity description: Briesen is a small town in present-day Germany best known as the birthplace of Nobel Prize–winning chemist Walther Nernst.
-
A.
Günsberg
Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
-
B.
Böbing
Böbing is a small municipality in the Weilheim-Schongau district of Bavaria, Germany, known for its rural setting in the Alpine foothills.
-
C.
Rheydt
Rheydt is a district of the German city of Mönchengladbach in North Rhine-Westphalia, historically an independent town in the Rhineland.
-
D.
Biebrich
Biebrich is a district of Wiesbaden in the German state of Hesse, historically known as an independent town on the Rhine and the site of the Baroque Biebrich Palace.
-
E.
Radevormwald
Radevormwald is a small historic town in North Rhine-Westphalia, western Germany, known for its hilly Bergisches Land landscape and traditional textile and metalworking industries.
- F. None of above. chosen
Provenance (5 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_69a885ffc5ec819091afa325d5f9611c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9098f384c81909ef836ee779466e2 |
completed | March 5, 2026, 4:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae02fd8f68819080a4b39ce3ad1198 |
completed | March 8, 2026, 11:15 p.m. |
| NEDg | Description generation | batch_69ae0354854c8190873938e03d56db21 |
completed | March 8, 2026, 11:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae039c7728819086acf060afcbe5b6 |
completed | March 8, 2026, 11:17 p.m. |
Created at: March 4, 2026, 7:28 p.m.