Triple
T9010340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Landkreis Günzburg |
E215451
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Nattenhausen
Nattenhausen is a small village in the Bavarian district of Günzburg in southern Germany.
|
E823978
|
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: Nattenhausen | Statement: [Landkreis Günzburg, contains, Nattenhausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nattenhausen Context triple: [Landkreis Günzburg, contains, Nattenhausen]
-
A.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
B.
Thannhausen
Thannhausen is a small town in the Bavarian region of Swabia in southern Germany.
-
C.
Irschenhausen
Irschenhausen is a small village in Bavaria, Germany, known in part as the place where German field marshal Erich von Manstein died.
-
D.
Deisenhausen
Deisenhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
E.
Warthausen
Warthausen is a small municipality in the district of Biberach in the German state of Baden-Württemberg, known for its historic castle and rural setting.
- 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: Nattenhausen Triple: [Landkreis Günzburg, contains, Nattenhausen]
Generated description
Nattenhausen is a small village in the Bavarian district of Günzburg in southern Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nattenhausen Target entity description: Nattenhausen is a small village in the Bavarian district of Günzburg in southern Germany.
-
A.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
B.
Thannhausen
Thannhausen is a small town in the Bavarian region of Swabia in southern Germany.
-
C.
Irschenhausen
Irschenhausen is a small village in Bavaria, Germany, known in part as the place where German field marshal Erich von Manstein died.
-
D.
Deisenhausen
Deisenhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
E.
Warthausen
Warthausen is a small municipality in the district of Biberach in the German state of Baden-Württemberg, known for its historic castle and rural setting.
- 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_69ca83a2bf088190986ee7a8eb90407d |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc69c1571881908d0b144786b5ee1f |
completed | April 1, 2026, 12:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1d58be8a4819088c419888a879e3e |
completed | April 5, 2026, 3:22 a.m. |
| NEDg | Description generation | batch_69d1d603a2948190a16ace344bdba057 |
completed | April 5, 2026, 3:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1d6578a048190bc05c4a8a1aa854f |
completed | April 5, 2026, 3:26 a.m. |
Created at: March 30, 2026, 7:06 p.m.