Triple
T4092159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jensen's inequality |
E87727
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object |
Johan Jensen
Johan Jensen was a Danish mathematician best known for his contributions to convex analysis and for formulating the inequality that bears his name.
|
E412924
|
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: Johan Jensen | Statement: [Jensen's inequality, namedAfter, Johan Jensen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Johan Jensen Context triple: [Jensen's inequality, namedAfter, Johan Jensen]
-
A.
Niels Jensen
Niels Jensen is a software entrepreneur best known as one of the founders of the software company Borland.
-
B.
Armin Hansen
Armin Hansen was an American painter known for his dynamic marine scenes and contributions to early 20th-century California art.
-
C.
Sven Simonsen
Sven Simonsen is an entrepreneur best known as a founder of the semiconductor company Advanced Micro Devices (AMD).
-
D.
Helge Petersen
Helge Petersen was a mountaineer known for making the first recorded ascent of Greenland’s highest peak, Gunnbjørn Fjeld.
-
E.
Joachim Lemelsen
Joachim Lemelsen was a German Wehrmacht general during World War II who held several high-ranking field commands on the Eastern and Italian fronts.
- 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: Johan Jensen Triple: [Jensen's inequality, namedAfter, Johan Jensen]
Generated description
Johan Jensen was a Danish mathematician best known for his contributions to convex analysis and for formulating the inequality that bears his name.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Johan Jensen Target entity description: Johan Jensen was a Danish mathematician best known for his contributions to convex analysis and for formulating the inequality that bears his name.
-
A.
Niels Jensen
Niels Jensen is a software entrepreneur best known as one of the founders of the software company Borland.
-
B.
Armin Hansen
Armin Hansen was an American painter known for his dynamic marine scenes and contributions to early 20th-century California art.
-
C.
Sven Simonsen
Sven Simonsen is an entrepreneur best known as a founder of the semiconductor company Advanced Micro Devices (AMD).
-
D.
Helge Petersen
Helge Petersen was a mountaineer known for making the first recorded ascent of Greenland’s highest peak, Gunnbjørn Fjeld.
-
E.
Joachim Lemelsen
Joachim Lemelsen was a German Wehrmacht general during World War II who held several high-ranking field commands on the Eastern and Italian fronts.
- 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_69aed94425148190be337845d56fac22 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefcae22a081908af65a960306b78c |
completed | March 9, 2026, 5 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b56b6cfb288190ac08c3a37327ac9a |
completed | March 14, 2026, 2:06 p.m. |
| NEDg | Description generation | batch_69b56cd11b5c8190b7e7c9c91b6564b6 |
completed | March 14, 2026, 2:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b56d3ff45881909f8b2c21ce51e0f0 |
completed | March 14, 2026, 2:14 p.m. |
Created at: March 9, 2026, 3:40 p.m.