Triple
T12597160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mertens’ theorems |
E300762
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object |
Franz Mertens
Franz Mertens was a 19th-century Austrian mathematician best known for his contributions to number theory, including results related to the Möbius function and the Mertens conjecture.
|
E992320
|
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: Franz Mertens | Statement: [Mertens’ theorems, namedAfter, Franz Mertens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Franz Mertens Context triple: [Mertens’ theorems, namedAfter, Franz Mertens]
-
A.
Tim Mertens
Tim Mertens is a film editor best known for his work on the animated feature "Big Hero 6."
-
B.
Éric Trappier
Éric Trappier is a French aerospace executive best known as the long-serving CEO and chairman of Dassault Aviation, overseeing programs such as the Rafale fighter jet.
-
C.
Tinus Osendarp
Tinus Osendarp was a Dutch sprinter best known for winning two bronze medals in the 100 m and 200 m events at the 1936 Berlin Olympics.
-
D.
Michael Mertens
Michael Mertens is a member of the German industrial metal band Propaganda.
-
E.
Michael Mertens
Michael Mertens is a writer known for his work on the character Dr. Mabuse.
- 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: Franz Mertens Triple: [Mertens’ theorems, namedAfter, Franz Mertens]
Generated description
Franz Mertens was a 19th-century Austrian mathematician best known for his contributions to number theory, including results related to the Möbius function and the Mertens conjecture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Franz Mertens Target entity description: Franz Mertens was a 19th-century Austrian mathematician best known for his contributions to number theory, including results related to the Möbius function and the Mertens conjecture.
-
A.
Tim Mertens
Tim Mertens is a film editor best known for his work on the animated feature "Big Hero 6."
-
B.
Éric Trappier
Éric Trappier is a French aerospace executive best known as the long-serving CEO and chairman of Dassault Aviation, overseeing programs such as the Rafale fighter jet.
-
C.
Tinus Osendarp
Tinus Osendarp was a Dutch sprinter best known for winning two bronze medals in the 100 m and 200 m events at the 1936 Berlin Olympics.
-
D.
Michael Mertens
Michael Mertens is a member of the German industrial metal band Propaganda.
-
E.
Michael Mertens
Michael Mertens is a writer known for his work on the character Dr. Mabuse.
- 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_69d7bdea2ca881908f379526c13b1145 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954cf33b88190bff339fcd3142cc8 |
completed | April 10, 2026, 7:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65ec75fc08190aa13cbb0161eb35c |
completed | May 2, 2026, 8:29 p.m. |
| NEDg | Description generation | batch_69f6605bca10819086966e1574c31318 |
completed | May 2, 2026, 8:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6617997188190bfce14c54619af7f |
completed | May 2, 2026, 8:41 p.m. |
Created at: April 9, 2026, 5:08 p.m.