Triple
T2053538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John A. Roebling |
E45622
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object |
Mühlhausen
Mühlhausen is a historic town in central Germany, known for its well-preserved medieval architecture and cultural heritage.
|
E351668
|
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: Mühlhausen | Statement: [John A. Roebling, placeOfBirth, Mühlhausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mühlhausen Context triple: [John A. Roebling, placeOfBirth, Mühlhausen]
-
A.
Markranstädt
Markranstädt is a small town in the German state of Saxony, located near Leipzig and known for its local industry and proximity to the Kulkwitzer See recreation area.
-
B.
Günzburg
Günzburg is a small Bavarian town in southern Germany, historically notable as the birthplace of Nazi physician Josef Mengele.
-
C.
Eisenach
Eisenach is a historic town in central Germany best known for its associations with Martin Luther and as the birthplace of composer Johann Sebastian Bach.
-
D.
Saalfeld
Saalfeld is a town in the German state of Thuringia, known for its historic old town and former significance as a regional railway and industrial center.
-
E.
Kitzingen
Kitzingen is a historic town in northern Bavaria, Germany, known for its wine production and location along the Main 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: Mühlhausen Triple: [John A. Roebling, placeOfBirth, Mühlhausen]
Generated description
Mühlhausen is a historic town in central Germany, known for its well-preserved medieval architecture and cultural heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mühlhausen Target entity description: Mühlhausen is a historic town in central Germany, known for its well-preserved medieval architecture and cultural heritage.
-
A.
Markranstädt
Markranstädt is a small town in the German state of Saxony, located near Leipzig and known for its local industry and proximity to the Kulkwitzer See recreation area.
-
B.
Günzburg
Günzburg is a small Bavarian town in southern Germany, historically notable as the birthplace of Nazi physician Josef Mengele.
-
C.
Eisenach
Eisenach is a historic town in central Germany best known for its associations with Martin Luther and as the birthplace of composer Johann Sebastian Bach.
-
D.
Saalfeld
Saalfeld is a town in the German state of Thuringia, known for its historic old town and former significance as a regional railway and industrial center.
-
E.
Kitzingen
Kitzingen is a historic town in northern Bavaria, Germany, known for its wine production and location along the Main 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_69a8891a19508190a12ef1e192308dcb |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb99196ec819096f491ac7732156a |
completed | March 7, 2026, 5:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b324b9ba9c8190bfba5d7539cffeb2 |
completed | March 12, 2026, 8:40 p.m. |
| NEDg | Description generation | batch_69b32882dbc481908998c6d9e8dfc007 |
completed | March 12, 2026, 8:56 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b32974082881909d6e8bc8e5e71bc0 |
completed | March 12, 2026, 9 p.m. |
Created at: March 4, 2026, 7:39 p.m.