Triple
T9728064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | district of Altötting |
E235664
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Wald an der Alz
Wald an der Alz is a small municipality in southeastern Bavaria, Germany, situated along the Alz River and known for its rural character and scenic surroundings.
|
E816646
|
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: Wald an der Alz | Statement: [district of Altötting, contains, Wald an der Alz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wald an der Alz Context triple: [district of Altötting, contains, Wald an der Alz]
-
A.
Lülsfeld
Lülsfeld is a small municipality in the Schweinfurt district of Lower Franconia in northern Bavaria, Germany.
-
B.
Ziegenhain
Ziegenhain is a historic town in the German state of Hesse, known for its medieval fortifications and role in regional conflicts.
-
C.
Waldbröl
Waldbröl is a small town in North Rhine-Westphalia, Germany, known for its rural setting in the Bergisches Land region.
-
D.
Trostberg
Trostberg is a small Bavarian town in southeastern Germany known for its historic old town and chemical industry.
-
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: Wald an der Alz Triple: [district of Altötting, contains, Wald an der Alz]
Generated description
Wald an der Alz is a small municipality in southeastern Bavaria, Germany, situated along the Alz River and known for its rural character and scenic surroundings.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wald an der Alz Target entity description: Wald an der Alz is a small municipality in southeastern Bavaria, Germany, situated along the Alz River and known for its rural character and scenic surroundings.
-
A.
Lülsfeld
Lülsfeld is a small municipality in the Schweinfurt district of Lower Franconia in northern Bavaria, Germany.
-
B.
Ziegenhain
Ziegenhain is a historic town in the German state of Hesse, known for its medieval fortifications and role in regional conflicts.
-
C.
Waldbröl
Waldbröl is a small town in North Rhine-Westphalia, Germany, known for its rural setting in the Bergisches Land region.
-
D.
Trostberg
Trostberg is a small Bavarian town in southeastern Germany known for its historic old town and chemical industry.
-
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_69ca84d0fad481909cdd45aa77416c48 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9e7af544819090a8a1adec41943c |
completed | April 1, 2026, 10:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d19fb208a48190864f8f085da83db7 |
completed | April 4, 2026, 11:33 p.m. |
| NEDg | Description generation | batch_69d1a1057e0c819096cc0984c9a83bb9 |
completed | April 4, 2026, 11:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1a184af3081908ce2932218244e7d |
completed | April 4, 2026, 11:40 p.m. |
Created at: March 30, 2026, 8:21 p.m.