Triple
T11116036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Clemens, Michigan |
E262886
|
entity |
| Predicate | namedFor |
P63
|
FINISHED |
| Object |
Christian Clemens
Christian Clemens was an early settler and prominent landowner whose influence led to the naming of Mount Clemens, Michigan.
|
E905223
|
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: Christian Clemens | Statement: [Mount Clemens, Michigan, namedFor, Christian Clemens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christian Clemens Context triple: [Mount Clemens, Michigan, namedFor, Christian Clemens]
-
A.
Christian Specht
Christian Specht is a German politician who serves as the mayor of the city of Mannheim.
-
B.
Michael Schaefer
Michael Schaefer is a film and television producer known for his executive production work on projects such as the series "Swarm."
-
C.
Christian Clemenson
Christian Clemenson is an American actor best known for his Emmy-winning role on "Boston Legal" and numerous character roles in film and television.
-
D.
Erik Heinrichs
Erik Heinrichs was a Finnish general and senior military leader who played a key role in directing Finland’s armed forces during World War II.
-
E.
Michael Philipp Boumann
Michael Philipp Boumann was a German architect best known for his work on prominent Prussian buildings in the late 18th and early 19th centuries.
- 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: Christian Clemens Triple: [Mount Clemens, Michigan, namedFor, Christian Clemens]
Generated description
Christian Clemens was an early settler and prominent landowner whose influence led to the naming of Mount Clemens, Michigan.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Christian Clemens Target entity description: Christian Clemens was an early settler and prominent landowner whose influence led to the naming of Mount Clemens, Michigan.
-
A.
Christian Specht
Christian Specht is a German politician who serves as the mayor of the city of Mannheim.
-
B.
Michael Schaefer
Michael Schaefer is a film and television producer known for his executive production work on projects such as the series "Swarm."
-
C.
Christian Clemenson
Christian Clemenson is an American actor best known for his Emmy-winning role on "Boston Legal" and numerous character roles in film and television.
-
D.
Erik Heinrichs
Erik Heinrichs was a Finnish general and senior military leader who played a key role in directing Finland’s armed forces during World War II.
-
E.
Michael Philipp Boumann
Michael Philipp Boumann was a German architect best known for his work on prominent Prussian buildings in the late 18th and early 19th centuries.
- 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_69d6aa9b46cc8190b19f9f0cc45bf322 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79aa81d8c81908a387b56cbcc9128 |
completed | April 9, 2026, 12:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e42d7da99881908d38ea66c37dfb92 |
completed | April 19, 2026, 1:18 a.m. |
| NEDg | Description generation | batch_69e42e67724481908bd9e73487a80d44 |
completed | April 19, 2026, 1:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e4308103c48190b32ee3047d9a0860 |
completed | April 19, 2026, 1:31 a.m. |
Created at: April 8, 2026, 9:27 p.m.