Triple
T18068319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Werdau |
E432350
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Langenhessen
Langenhessen is a district or locality that forms part of the town of Werdau in the German state of Saxony.
|
E1330859
|
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: Langenhessen | Statement: [Werdau, hasSubdivision, Langenhessen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Langenhessen Context triple: [Werdau, hasSubdivision, Langenhessen]
-
A.
Hildburghausen
Hildburghausen is a town in the German state of Thuringia that historically served as the residence of the dukes of Saxe-Hildburghausen.
-
B.
Höchheim
Höchheim is a small municipality in the Rhön-Grabfeld district of northern Bavaria, Germany.
-
C.
Grafenrheinfeld
Grafenrheinfeld is a small Bavarian town best known for hosting the former Grafenrheinfeld nuclear power plant on the Main River in northern Germany.
-
D.
Abensberg
Abensberg is a historic town in Bavaria, Germany, known for its medieval architecture and its role as a Napoleonic-era battlefield.
-
E.
Gerlachsheim
Gerlachsheim is a district of the town Lauda-Königshofen in the Main-Tauber-Kreis region of Baden-Württemberg, Germany.
- 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: Langenhessen Triple: [Werdau, hasSubdivision, Langenhessen]
Generated description
Langenhessen is a district or locality that forms part of the town of Werdau in the German state of Saxony.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Langenhessen Target entity description: Langenhessen is a district or locality that forms part of the town of Werdau in the German state of Saxony.
-
A.
Hildburghausen
Hildburghausen is a town in the German state of Thuringia that historically served as the residence of the dukes of Saxe-Hildburghausen.
-
B.
Höchheim
Höchheim is a small municipality in the Rhön-Grabfeld district of northern Bavaria, Germany.
-
C.
Grafenrheinfeld
Grafenrheinfeld is a small Bavarian town best known for hosting the former Grafenrheinfeld nuclear power plant on the Main River in northern Germany.
-
D.
Abensberg
Abensberg is a historic town in Bavaria, Germany, known for its medieval architecture and its role as a Napoleonic-era battlefield.
-
E.
Gerlachsheim
Gerlachsheim is a district of the town Lauda-Königshofen in the Main-Tauber-Kreis region of Baden-Württemberg, Germany.
- 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_69d8b9070cac81909fa9473fb1c3f1c7 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4cceb020081909329492591e7b1f2 |
completed | April 19, 2026, 12:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a049abe0f5c81909bee53d18f186e0c |
completed | May 13, 2026, 3:37 p.m. |
| NEDg | Description generation | batch_6a049c461c288190955ac8cdaefc055d |
completed | May 13, 2026, 3:44 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a049cbbc0288190be82f11e660b7dff |
completed | May 13, 2026, 3:46 p.m. |
Created at: April 10, 2026, 10:26 a.m.