Triple
T657510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lichtenfels |
E11679
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Unterwallenstadt
Unterwallenstadt is a small locality that forms part of the town of Lichtenfels in the Upper Franconia region of Bavaria, Germany.
|
E104974
|
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: Unterwallenstadt | Statement: [Lichtenfels, hasSubdivision, Unterwallenstadt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Unterwallenstadt Context triple: [Lichtenfels, hasSubdivision, Unterwallenstadt]
-
A.
Oberwallenstadt
Oberwallenstadt is a village and district of the town of Lichtenfels in the Upper Franconia region of Bavaria, Germany.
-
B.
Büllingen
Büllingen is a municipality in eastern Belgium’s German-speaking Community, known for its rural landscape and proximity to the historically significant Elsenborn Ridge.
-
C.
Lommersweiler
Lommersweiler is a village and municipal section of the town of St. Vith in the German-speaking Community of eastern Belgium.
-
D.
Stetten
Stetten is a locality within the town of Lichtenfels in the German state of Bavaria.
-
E.
Boblingen
Böblingen is a town in the German state of Baden-Württemberg, known for its automotive industry presence and proximity to Stuttgart.
- 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: Unterwallenstadt Triple: [Lichtenfels, hasSubdivision, Unterwallenstadt]
Generated description
Unterwallenstadt is a small locality that forms part of the town of Lichtenfels in the Upper Franconia region of Bavaria, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Unterwallenstadt Target entity description: Unterwallenstadt is a small locality that forms part of the town of Lichtenfels in the Upper Franconia region of Bavaria, Germany.
-
A.
Oberwallenstadt
Oberwallenstadt is a village and district of the town of Lichtenfels in the Upper Franconia region of Bavaria, Germany.
-
B.
Büllingen
Büllingen is a municipality in eastern Belgium’s German-speaking Community, known for its rural landscape and proximity to the historically significant Elsenborn Ridge.
-
C.
Lommersweiler
Lommersweiler is a village and municipal section of the town of St. Vith in the German-speaking Community of eastern Belgium.
-
D.
Stetten
Stetten is a locality within the town of Lichtenfels in the German state of Bavaria.
-
E.
Boblingen
Böblingen is a town in the German state of Baden-Württemberg, known for its automotive industry presence and proximity to Stuttgart.
- 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_69a4932862a0819098be659c814e4981 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49fa55e048190bd9913c6c31772d0 |
completed | March 1, 2026, 8:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7c0036a5081909d5b3a81a9ef3daf |
completed | March 4, 2026, 5:15 a.m. |
| NEDg | Description generation | batch_69a7c0716e708190b907502b17b671f8 |
completed | March 4, 2026, 5:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a7c0d166ac819089b683e7cee92043 |
completed | March 4, 2026, 5:19 a.m. |
Created at: March 1, 2026, 7:36 p.m.