Triple
T15502966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | arrondissement of Mulhouse |
E379006
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Wittenheim
Wittenheim is a commune in the Haut-Rhin department of northeastern France, situated near Mulhouse in the historical region of Alsace.
|
E1161641
|
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: Wittenheim | Statement: [arrondissement of Mulhouse, contains, Wittenheim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wittenheim Context triple: [arrondissement of Mulhouse, contains, Wittenheim]
-
A.
Viernheim
Viernheim is a town in the state of Hesse in southwestern Germany, known as a residential and commercial center within the Rhine-Neckar metropolitan region.
-
B.
Willebadessen
Willebadessen is a small town in western Germany, located in the state of North Rhine-Westphalia.
-
C.
Rheingönheim
Rheingönheim is a district of the industrial city of Ludwigshafen am Rhein in the German state of Rhineland-Palatinate.
-
D.
Frei-Weinheim
Frei-Weinheim is a district of the town Ingelheim am Rhein in Rhineland-Palatinate, Germany, situated along the Rhine River.
-
E.
Wustermark
Wustermark is a municipality in the Havelland district of Brandenburg, Germany, located west of Berlin and known for its mix of rural character and growing residential and commercial areas.
- 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: Wittenheim Triple: [arrondissement of Mulhouse, contains, Wittenheim]
Generated description
Wittenheim is a commune in the Haut-Rhin department of northeastern France, situated near Mulhouse in the historical region of Alsace.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wittenheim Target entity description: Wittenheim is a commune in the Haut-Rhin department of northeastern France, situated near Mulhouse in the historical region of Alsace.
-
A.
Viernheim
Viernheim is a town in the state of Hesse in southwestern Germany, known as a residential and commercial center within the Rhine-Neckar metropolitan region.
-
B.
Willebadessen
Willebadessen is a small town in western Germany, located in the state of North Rhine-Westphalia.
-
C.
Rheingönheim
Rheingönheim is a district of the industrial city of Ludwigshafen am Rhein in the German state of Rhineland-Palatinate.
-
D.
Frei-Weinheim
Frei-Weinheim is a district of the town Ingelheim am Rhein in Rhineland-Palatinate, Germany, situated along the Rhine River.
-
E.
Wustermark
Wustermark is a municipality in the Havelland district of Brandenburg, Germany, located west of Berlin and known for its mix of rural character and growing residential and commercial areas.
- 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fcc5bb88190b8a9a81419a9a38b |
completed | April 16, 2026, 1:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3d4a9bf88190b7c6b4874abe165f |
completed | May 9, 2026, 1:57 p.m. |
| NEDg | Description generation | batch_69ff3e77330881909f13327aa2616203 |
completed | May 9, 2026, 2:02 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff3eed56b881908363380284e9d81b |
completed | May 9, 2026, 2:04 p.m. |
Created at: April 10, 2026, 3:54 a.m.