Triple
T7295301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nadelhorn |
E164505
|
entity |
| Predicate | firstAscentBy |
P1321
|
FINISHED |
| Object |
Benedikt Supersaxo
Benedikt Supersaxo was a Swiss mountain guide and alpinist known for pioneering ascents in the Pennine Alps during the 19th century.
|
E654716
|
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: Benedikt Supersaxo | Statement: [Nadelhorn, firstAscentBy, Benedikt Supersaxo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Benedikt Supersaxo Context triple: [Nadelhorn, firstAscentBy, Benedikt Supersaxo]
-
A.
Markus Sattler
Markus Sattler is a German software engineer and entrepreneur best known as a co-founder and former CTO of the email marketing platform Mailjet.
-
B.
Stephan Sauer
Stephan Sauer is a notable individual who shares the surname Sauer and is recognized for achievements significant enough to be specifically referenced.
-
C.
Christoph Sauer
Christoph Sauer was an 18th-century German-American printer and publisher known for producing one of the earliest German-language Bibles in North America.
-
D.
Andreas Ochs
Andreas Ochs is a German professional football goalkeeper known for playing in the German league system.
-
E.
Sven Wagner
Sven Wagner is a German local politician who serves as the mayor of the town of Aschersleben in Saxony-Anhalt.
- 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: Benedikt Supersaxo Triple: [Nadelhorn, firstAscentBy, Benedikt Supersaxo]
Generated description
Benedikt Supersaxo was a Swiss mountain guide and alpinist known for pioneering ascents in the Pennine Alps during the 19th century.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Benedikt Supersaxo Target entity description: Benedikt Supersaxo was a Swiss mountain guide and alpinist known for pioneering ascents in the Pennine Alps during the 19th century.
-
A.
Markus Sattler
Markus Sattler is a German software engineer and entrepreneur best known as a co-founder and former CTO of the email marketing platform Mailjet.
-
B.
Stephan Sauer
Stephan Sauer is a notable individual who shares the surname Sauer and is recognized for achievements significant enough to be specifically referenced.
-
C.
Christoph Sauer
Christoph Sauer was an 18th-century German-American printer and publisher known for producing one of the earliest German-language Bibles in North America.
-
D.
Andreas Ochs
Andreas Ochs is a German professional football goalkeeper known for playing in the German league system.
-
E.
Sven Wagner
Sven Wagner is a German local politician who serves as the mayor of the town of Aschersleben in Saxony-Anhalt.
- 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_69c6887a499881909dd23341399c59d8 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6eb8d0c6c8190b32cd08b9a5d96cc |
completed | March 27, 2026, 8:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7e543c22c8190acf8dcffd9c59520 |
completed | March 28, 2026, 2:27 p.m. |
| NEDg | Description generation | batch_69c7e5df5eb08190a22e53b95fbc23f2 |
completed | March 28, 2026, 2:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7e64fe200819081901b32523a5fa5 |
completed | March 28, 2026, 2:31 p.m. |
Created at: March 27, 2026, 3 p.m.