Triple
T7259452
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Grünberg |
E159609
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Grünberg |
E392482
|
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: Grünberg | Statement: [Peter Grünberg, familyName, Grünberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grünberg Context triple: [Peter Grünberg, familyName, Grünberg]
-
A.
Grünberg
chosen
Grünberg is a small German town in the state of Hesse, known for its historic half-timbered old town and traditional regional festivals.
-
B.
Grüneberg
Grüneberg is a locality in Germany historically known as the site of the Battle of Grüneberg.
-
C.
Miltenberg
Miltenberg is a historic town in Bavaria, Germany, known for its well-preserved medieval old town along the Main River and its timber-framed architecture.
-
D.
Biesenthal
Biesenthal is a small town in the Barnim district of Brandenburg, Germany, known for its surrounding lakes, forests, and location within the Barnim Nature Park.
-
E.
Luxenberg
Luxenberg is an alternative spelling or variant form of the name "Luxemburg," which can refer to the European country Luxembourg or the surname of notable individuals such as revolutionary Rosa Luxemburg.
- 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_69c68838f9948190875fd60b2351230c |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eac340a0819084015a5fbf7a5539 |
completed | March 27, 2026, 8:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7d3b99af08190a28d77e7363edf45 |
completed | March 28, 2026, 1:12 p.m. |
Created at: March 27, 2026, 2:57 p.m.