Triple
T9208390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | District of Weilheim-Schongau |
E221046
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object |
Iffeldorf
Iffeldorf is a small Bavarian municipality in southern Germany known for its scenic lake district and rural character.
|
E799063
|
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: Iffeldorf | Statement: [District of Weilheim-Schongau, containsMunicipality, Iffeldorf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Iffeldorf Context triple: [District of Weilheim-Schongau, containsMunicipality, Iffeldorf]
-
A.
Lülsfeld
Lülsfeld is a small municipality in the Schweinfurt district of Lower Franconia in northern Bavaria, Germany.
-
B.
Hasselfelde
Hasselfelde is a small town in the Harz region of central Germany, now incorporated into the municipality of Oberharz am Brocken.
-
C.
Breckerfeld
Breckerfeld is a small town in North Rhine-Westphalia, Germany, known for its rural character and location in the hilly, forested region of the Sauerland.
-
D.
Pfullendorf
Pfullendorf is a historic town in the state of Baden-Württemberg in southern Germany, known for its well-preserved medieval old town.
-
E.
Neuendorf
Neuendorf is a small village on the Baltic Sea island of Hiddensee in Germany, known for its traditional thatched houses and maritime character.
- 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: Iffeldorf Triple: [District of Weilheim-Schongau, containsMunicipality, Iffeldorf]
Generated description
Iffeldorf is a small Bavarian municipality in southern Germany known for its scenic lake district and rural character.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Iffeldorf Target entity description: Iffeldorf is a small Bavarian municipality in southern Germany known for its scenic lake district and rural character.
-
A.
Lülsfeld
Lülsfeld is a small municipality in the Schweinfurt district of Lower Franconia in northern Bavaria, Germany.
-
B.
Hasselfelde
Hasselfelde is a small town in the Harz region of central Germany, now incorporated into the municipality of Oberharz am Brocken.
-
C.
Breckerfeld
Breckerfeld is a small town in North Rhine-Westphalia, Germany, known for its rural character and location in the hilly, forested region of the Sauerland.
-
D.
Pfullendorf
Pfullendorf is a historic town in the state of Baden-Württemberg in southern Germany, known for its well-preserved medieval old town.
-
E.
Neuendorf
Neuendorf is a small village on the Baltic Sea island of Hiddensee in Germany, known for its traditional thatched houses and maritime character.
- 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_69ca83e9d0e081908bdb71097201a06c |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd9b217008190a0ab4971dd4a8899 |
completed | April 1, 2026, 8:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d110107c4c819091037d83362b0021 |
completed | April 4, 2026, 1:20 p.m. |
| NEDg | Description generation | batch_69d110eeddc881908661d110269b8a1c |
completed | April 4, 2026, 1:23 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d111f3190c8190ba2fe5687212da25 |
completed | April 4, 2026, 1:28 p.m. |
Created at: March 30, 2026, 7:26 p.m.