Triple
T8066198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | District of Mittelsachsen |
E188248
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Hainichen
Hainichen is a small town in the Free State of Saxony in eastern Germany, known for its historical architecture and location between the cities of Chemnitz and Dresden.
|
E715515
|
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: Hainichen | Statement: [District of Mittelsachsen, contains, Hainichen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hainichen Context triple: [District of Mittelsachsen, contains, Hainichen]
-
A.
Hohne
Hohne is a village in Lower Saxony, Germany, historically notable for its military garrison and association with British Army units.
-
B.
Todenfeld
Todenfeld is a village and district of the town of Rheinbach in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
-
C.
Seckbach
Seckbach is a district in the east of Frankfurt am Main, Germany, known for its residential character and proximity to green spaces like the Lohrberg.
-
D.
Naunhof
Naunhof is a small town in the Free State of Saxony in eastern Germany, known for its surrounding lakes and forests near the city of Leipzig.
-
E.
Ziegenhain
Ziegenhain is a historic town in the German state of Hesse, known for its medieval fortifications and role in regional conflicts.
- 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: Hainichen Triple: [District of Mittelsachsen, contains, Hainichen]
Generated description
Hainichen is a small town in the Free State of Saxony in eastern Germany, known for its historical architecture and location between the cities of Chemnitz and Dresden.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hainichen Target entity description: Hainichen is a small town in the Free State of Saxony in eastern Germany, known for its historical architecture and location between the cities of Chemnitz and Dresden.
-
A.
Hohne
Hohne is a village in Lower Saxony, Germany, historically notable for its military garrison and association with British Army units.
-
B.
Todenfeld
Todenfeld is a village and district of the town of Rheinbach in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
-
C.
Seckbach
Seckbach is a district in the east of Frankfurt am Main, Germany, known for its residential character and proximity to green spaces like the Lohrberg.
-
D.
Naunhof
Naunhof is a small town in the Free State of Saxony in eastern Germany, known for its surrounding lakes and forests near the city of Leipzig.
-
E.
Ziegenhain
Ziegenhain is a historic town in the German state of Hesse, known for its medieval fortifications and role in regional conflicts.
- 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_69ca82b42674819086840efea12478e5 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3ff5547c8190a7ec5958a23e302f |
completed | March 31, 2026, 3:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccbe67d9dc8190ad72e3f5ce7478e3 |
completed | April 1, 2026, 6:42 a.m. |
| NEDg | Description generation | batch_69ccc30f1fc48190991e0caa9ea6e735 |
completed | April 1, 2026, 7:02 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ccd7eca618819081e0c5452c8b1960 |
completed | April 1, 2026, 8:31 a.m. |
Created at: March 30, 2026, 5:26 p.m.