Triple
T21382686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tussenhausen |
E527401
|
entity |
| Predicate | hasVillage |
P4011
|
FINISHED |
| Object |
Zaisertshofen
Zaisertshofen is a small village in the municipality of Tussenhausen in Bavaria, Germany.
|
E1487353
|
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: Zaisertshofen | Statement: [Tussenhausen, hasVillage, Zaisertshofen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zaisertshofen Context triple: [Tussenhausen, hasVillage, Zaisertshofen]
-
A.
Zierolshofen
Zierolshofen is a village and district of the town of Kehl in the Ortenaukreis region of Baden-Württemberg, Germany.
-
B.
Reichertshofen
Reichertshofen is a market town and municipality in Upper Bavaria, Germany, known for its location near the confluence of the Paar and Ilm rivers and its proximity to the city of Ingolstadt.
-
C.
Gerolzhofen
Gerolzhofen is a small historic town in northern Bavaria, Germany, known for its medieval architecture and wine-growing surroundings.
-
D.
Odelshofen
Odelshofen is a village and district (Ortsteil) of the town of Kehl in the state of Baden-Württemberg, Germany.
-
E.
Vilgertshofen
Vilgertshofen is a small rural municipality in the Bavarian region of Germany, characterized by its agricultural landscape and village-style community.
- 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: Zaisertshofen Triple: [Tussenhausen, hasVillage, Zaisertshofen]
Generated description
Zaisertshofen is a small village in the municipality of Tussenhausen in Bavaria, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Zaisertshofen Target entity description: Zaisertshofen is a small village in the municipality of Tussenhausen in Bavaria, Germany.
-
A.
Zierolshofen
Zierolshofen is a village and district of the town of Kehl in the Ortenaukreis region of Baden-Württemberg, Germany.
-
B.
Reichertshofen
Reichertshofen is a market town and municipality in Upper Bavaria, Germany, known for its location near the confluence of the Paar and Ilm rivers and its proximity to the city of Ingolstadt.
-
C.
Gerolzhofen
Gerolzhofen is a small historic town in northern Bavaria, Germany, known for its medieval architecture and wine-growing surroundings.
-
D.
Odelshofen
Odelshofen is a village and district (Ortsteil) of the town of Kehl in the state of Baden-Württemberg, Germany.
-
E.
Vilgertshofen
Vilgertshofen is a small rural municipality in the Bavarian region of Germany, characterized by its agricultural landscape and village-style community.
- 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_69e0b51f363c8190944000ab5523b02b |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b0d1fa1c8190b3374e0bb3a971fc |
completed | April 22, 2026, 11:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09e12440b08190b50913782a47e144 |
completed | May 17, 2026, 3:39 p.m. |
| NEDg | Description generation | batch_6a09e1d4a6bc8190909ca0e358e35c85 |
completed | May 17, 2026, 3:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09e22dcac081909a02bbb3f74f42a9 |
completed | May 17, 2026, 3:43 p.m. |
Created at: April 16, 2026, 5:12 p.m.