Triple
T7685714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kai Siegbahn |
E174109
|
entity |
| Predicate | notableStudent |
P4838
|
FINISHED |
| Object |
Jens Als-Nielsen
Jens Als-Nielsen is a Danish physicist known for his contributions to condensed matter physics and X-ray scattering techniques.
|
E689247
|
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: Jens Als-Nielsen | Statement: [Kai Siegbahn, notableStudent, Jens Als-Nielsen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jens Als-Nielsen Context triple: [Kai Siegbahn, notableStudent, Jens Als-Nielsen]
-
A.
Thue Christiansen
Thue Christiansen was a Greenlandic teacher, artist, and politician best known for creating Greenland’s national flag.
-
B.
Niels Jensen
Niels Jensen is a software entrepreneur best known as one of the founders of the software company Borland.
-
C.
Flemming Hansen
Flemming Hansen is a Danish politician who served as a member of parliament and held several ministerial posts, including Minister of Transport.
-
D.
Jens Juel
Jens Juel was a prominent Danish portrait painter of the late 18th and early 19th centuries, renowned for his depictions of the Danish aristocracy and royal family.
-
E.
Helge Petersen
Helge Petersen was a mountaineer known for making the first recorded ascent of Greenland’s highest peak, Gunnbjørn Fjeld.
- 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: Jens Als-Nielsen Triple: [Kai Siegbahn, notableStudent, Jens Als-Nielsen]
Generated description
Jens Als-Nielsen is a Danish physicist known for his contributions to condensed matter physics and X-ray scattering techniques.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jens Als-Nielsen Target entity description: Jens Als-Nielsen is a Danish physicist known for his contributions to condensed matter physics and X-ray scattering techniques.
-
A.
Thue Christiansen
Thue Christiansen was a Greenlandic teacher, artist, and politician best known for creating Greenland’s national flag.
-
B.
Niels Jensen
Niels Jensen is a software entrepreneur best known as one of the founders of the software company Borland.
-
C.
Flemming Hansen
Flemming Hansen is a Danish politician who served as a member of parliament and held several ministerial posts, including Minister of Transport.
-
D.
Jens Juel
Jens Juel was a prominent Danish portrait painter of the late 18th and early 19th centuries, renowned for his depictions of the Danish aristocracy and royal family.
-
E.
Helge Petersen
Helge Petersen was a mountaineer known for making the first recorded ascent of Greenland’s highest peak, Gunnbjørn Fjeld.
- 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_69c6995840408190a19de6c51090f46f |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7022118908190a3a93cfda79be0a4 |
completed | March 27, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8f30c099081909aaeac321fbf0066 |
completed | March 29, 2026, 9:38 a.m. |
| NEDg | Description generation | batch_69c8f44b03088190beff15d159c5b98a |
completed | March 29, 2026, 9:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8f4c13be8819091a9022f0dc52bc9 |
completed | March 29, 2026, 9:45 a.m. |
Created at: March 27, 2026, 4:02 p.m.