Triple
T8790025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oberndorf am Neckar |
E209138
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Hochmössingen
Hochmössingen is a village in the German state of Baden-Württemberg that forms one of the districts of the town Oberndorf am Neckar.
|
E764011
|
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: Hochmössingen | Statement: [Oberndorf am Neckar, hasSubdivision, Hochmössingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hochmössingen Context triple: [Oberndorf am Neckar, hasSubdivision, Hochmössingen]
-
A.
Münsingen
Münsingen is a Swiss municipality in the canton of Bern, known for its scenic location in the Aare valley between Bern and Thun.
-
B.
Hohenmemmingen
Hohenmemmingen is a village-level subdivision of the town of Giengen an der Brenz in the German state of Baden-Württemberg.
-
C.
Menzingen
Menzingen is a municipality in the canton of Zug in central Switzerland, known for its rural landscape and location in the pre-Alpine region.
-
D.
Miesbach
Miesbach is a historic town in southern Germany known for its traditional Bavarian culture and picturesque Alpine foothill setting.
-
E.
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.
- 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: Hochmössingen Triple: [Oberndorf am Neckar, hasSubdivision, Hochmössingen]
Generated description
Hochmössingen is a village in the German state of Baden-Württemberg that forms one of the districts of the town Oberndorf am Neckar.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hochmössingen Target entity description: Hochmössingen is a village in the German state of Baden-Württemberg that forms one of the districts of the town Oberndorf am Neckar.
-
A.
Münsingen
Münsingen is a Swiss municipality in the canton of Bern, known for its scenic location in the Aare valley between Bern and Thun.
-
B.
Hohenmemmingen
Hohenmemmingen is a village-level subdivision of the town of Giengen an der Brenz in the German state of Baden-Württemberg.
-
C.
Menzingen
Menzingen is a municipality in the canton of Zug in central Switzerland, known for its rural landscape and location in the pre-Alpine region.
-
D.
Miesbach
Miesbach is a historic town in southern Germany known for its traditional Bavarian culture and picturesque Alpine foothill setting.
-
E.
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.
- 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_69ca836168108190bb43d3dc235c1f55 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f8d25f881908863d636fa57a8a2 |
completed | March 31, 2026, 11:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfab60ee608190af9f4aba631b42ef |
completed | April 3, 2026, 11:58 a.m. |
| NEDg | Description generation | batch_69cfac76d0f8819090c2bff520db52f4 |
completed | April 3, 2026, 12:03 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfad04e514819084bf30b8f026c031 |
completed | April 3, 2026, 12:05 p.m. |
Created at: March 30, 2026, 6:43 p.m.