Triple
T8600803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Landkreis Biberach |
E203668
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Eberhardzell
Eberhardzell is a rural municipality in the district of Biberach in the German state of Baden-Württemberg.
|
E767536
|
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: Eberhardzell | Statement: [Landkreis Biberach, hasMunicipality, Eberhardzell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eberhardzell Context triple: [Landkreis Biberach, hasMunicipality, Eberhardzell]
-
A.
Ebersberg
Ebersberg is a small Bavarian town and district capital east of Munich, known for its surrounding forest and traditional Upper Bavarian character.
-
B.
Steinlach
Steinlach is a small river in the German state of Baden-Württemberg that flows through the city of Tübingen before joining the Neckar.
-
C.
Kirchlindach
Kirchlindach is a Swiss municipality in the canton of Bern, known for its rural character and proximity to the city of Bern.
-
D.
Gerolzhofen
Gerolzhofen is a small historic town in northern Bavaria, Germany, known for its medieval architecture and wine-growing surroundings.
-
E.
Eggenfelden
Eggenfelden is a town in southeastern Germany known as a local commercial and cultural center within the region of Lower Bavaria.
- 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: Eberhardzell Triple: [Landkreis Biberach, hasMunicipality, Eberhardzell]
Generated description
Eberhardzell is a rural municipality in the district of Biberach in the German state of Baden-Württemberg.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Eberhardzell Target entity description: Eberhardzell is a rural municipality in the district of Biberach in the German state of Baden-Württemberg.
-
A.
Ebersberg
Ebersberg is a small Bavarian town and district capital east of Munich, known for its surrounding forest and traditional Upper Bavarian character.
-
B.
Steinlach
Steinlach is a small river in the German state of Baden-Württemberg that flows through the city of Tübingen before joining the Neckar.
-
C.
Kirchlindach
Kirchlindach is a Swiss municipality in the canton of Bern, known for its rural character and proximity to the city of Bern.
-
D.
Gerolzhofen
Gerolzhofen is a small historic town in northern Bavaria, Germany, known for its medieval architecture and wine-growing surroundings.
-
E.
Eggenfelden
Eggenfelden is a town in southeastern Germany known as a local commercial and cultural center within the region of Lower Bavaria.
- 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_69ca832b56948190ba751cec255308f1 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc46d8ff408190acc7cd8dc99b2689 |
completed | March 31, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc1b453908190ab00b7f3a3654491 |
completed | April 3, 2026, 1:33 p.m. |
| NEDg | Description generation | batch_69cfc2c1f1108190bfc68e4e174572d6 |
completed | April 3, 2026, 1:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfc39ebd7881909389905b47e98e71 |
completed | April 3, 2026, 1:41 p.m. |
Created at: March 30, 2026, 6:24 p.m.