Triple
T4711288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Much Wenlock |
E104516
|
entity |
| Predicate | twinnedWith |
P1072
|
FINISHED |
| Object |
Frohnhausen, Germany
Frohnhausen is a district in Germany known in part for its town-twinning partnership with Much Wenlock in England.
|
E464876
|
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: Frohnhausen, Germany | Statement: [Much Wenlock, twinnedWith, Frohnhausen, Germany]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frohnhausen, Germany Context triple: [Much Wenlock, twinnedWith, Frohnhausen, Germany]
-
A.
Friedberg, Germany
Friedberg, Germany is a historic town in the state of Hesse known for its medieval architecture, including a well-preserved castle and old town center.
-
B.
Schröttinghausen, Germany
Schröttinghausen is a small locality in Germany best known as the birthplace of influential astronomer Walter Baade.
-
C.
Pfaffenweiler, Germany
Pfaffenweiler is a small town in southwestern Germany known for its historical ties and sister-city relationship with Jasper, Indiana.
-
D.
Herzogenaurach, Germany
Herzogenaurach, Germany is a Bavarian town internationally known as the home base of major sportswear companies Adidas and Puma.
-
E.
Deggendorf, Germany
Deggendorf, Germany is a Bavarian town on the Danube River known as a regional commercial and industrial center with strong ties to manufacturing and technology companies.
- 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: Frohnhausen, Germany Triple: [Much Wenlock, twinnedWith, Frohnhausen, Germany]
Generated description
Frohnhausen is a district in Germany known in part for its town-twinning partnership with Much Wenlock in England.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Frohnhausen, Germany Target entity description: Frohnhausen is a district in Germany known in part for its town-twinning partnership with Much Wenlock in England.
-
A.
Friedberg, Germany
Friedberg, Germany is a historic town in the state of Hesse known for its medieval architecture, including a well-preserved castle and old town center.
-
B.
Schröttinghausen, Germany
Schröttinghausen is a small locality in Germany best known as the birthplace of influential astronomer Walter Baade.
-
C.
Pfaffenweiler, Germany
Pfaffenweiler is a small town in southwestern Germany known for its historical ties and sister-city relationship with Jasper, Indiana.
-
D.
Herzogenaurach, Germany
Herzogenaurach, Germany is a Bavarian town internationally known as the home base of major sportswear companies Adidas and Puma.
-
E.
Deggendorf, Germany
Deggendorf, Germany is a Bavarian town on the Danube River known as a regional commercial and industrial center with strong ties to manufacturing and technology companies.
- 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_69bd43eac3c08190af7e4020c6c3704c |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64049d6c8190be19935048fc6b14 |
completed | March 20, 2026, 3:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be1078784c81908e9a3fd0b168cadc |
completed | March 21, 2026, 3:28 a.m. |
| NEDg | Description generation | batch_69be11c41a7c81909f00d8301e224ec2 |
completed | March 21, 2026, 3:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be12497a90819086176bf8a8111517 |
completed | March 21, 2026, 3:36 a.m. |
Created at: March 20, 2026, 1:17 p.m.