Triple
T17414194
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meckesheim |
E423444
|
entity |
| Predicate | hasNeighboringMunicipality |
P224
|
FINISHED |
| Object |
Eschelbronn
Eschelbronn is a small municipality in the Rhein-Neckar district of Baden-Württemberg, Germany, known historically for its woodworking and furniture-making traditions.
|
E1292895
|
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: Eschelbronn | Statement: [Meckesheim, hasNeighboringMunicipality, Eschelbronn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eschelbronn Context triple: [Meckesheim, hasNeighboringMunicipality, Eschelbronn]
-
A.
Wechingen
Wechingen is a small rural municipality in the Bavarian region of southern Germany.
-
B.
Gernsbach
Gernsbach is a historic town in southwestern Germany’s Black Forest region, known for its medieval old town and picturesque setting along the Murg River.
-
C.
Ottmarsheim
Ottmarsheim is a commune in northeastern France’s Alsace region, known for its historic Romanesque church and location along the Rhine.
-
D.
Miesbach
Miesbach is a historic town in southern Germany known for its traditional Bavarian culture and picturesque Alpine foothill setting.
-
E.
Pfeffenhausen
Pfeffenhausen is a market town in Lower Bavaria, Germany, known for its rural character and location within the Landshut district.
- 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: Eschelbronn Triple: [Meckesheim, hasNeighboringMunicipality, Eschelbronn]
Generated description
Eschelbronn is a small municipality in the Rhein-Neckar district of Baden-Württemberg, Germany, known historically for its woodworking and furniture-making traditions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Eschelbronn Target entity description: Eschelbronn is a small municipality in the Rhein-Neckar district of Baden-Württemberg, Germany, known historically for its woodworking and furniture-making traditions.
-
A.
Wechingen
Wechingen is a small rural municipality in the Bavarian region of southern Germany.
-
B.
Gernsbach
Gernsbach is a historic town in southwestern Germany’s Black Forest region, known for its medieval old town and picturesque setting along the Murg River.
-
C.
Ottmarsheim
Ottmarsheim is a commune in northeastern France’s Alsace region, known for its historic Romanesque church and location along the Rhine.
-
D.
Miesbach
Miesbach is a historic town in southern Germany known for its traditional Bavarian culture and picturesque Alpine foothill setting.
-
E.
Pfeffenhausen
Pfeffenhausen is a market town in Lower Bavaria, Germany, known for its rural character and location within the Landshut district.
- 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_69d889d7d27c819088486ce3f0627fa1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e44230fc688190a6a7edc12d9e9947 |
completed | April 19, 2026, 2:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0313acae5c819095555194162f4b4f |
completed | May 12, 2026, 11:49 a.m. |
| NEDg | Description generation | batch_6a03140cbe248190bcccafcbeec8856e |
completed | May 12, 2026, 11:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a03146359f08190b5c5aec33dcc05d6 |
completed | May 12, 2026, 11:52 a.m. |
Created at: April 10, 2026, 5:46 a.m.