Triple
T14167190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Borchers |
E351110
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Detlev Borchers
Detlev Borchers is a German journalist and writer known for his work on technology, digital culture, and media.
|
E1083117
|
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: Detlev Borchers | Statement: [Borchers, hasNotableBearer, Detlev Borchers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Detlev Borchers Context triple: [Borchers, hasNotableBearer, Detlev Borchers]
-
A.
Hans-Peter Kriegel
Hans-Peter Kriegel is a German computer scientist renowned for his influential contributions to data mining and database systems, particularly in clustering and similarity search.
-
B.
Rainer G. Rümmler
Rainer G. Rümmler was a German architect best known for designing numerous distinctive Berlin U-Bahn stations in the latter half of the 20th century.
-
C.
Harald Ganzinger
Harald Ganzinger was a prominent German computer scientist known for his influential work in automated theorem proving and term rewriting systems.
-
D.
Gerhard Feige
Gerhard Feige is a German Roman Catholic prelate and theologian who serves as the bishop of Magdeburg.
-
E.
Dieter W. Heermann
Dieter W. Heermann is a physicist known for his work in computational physics and biophysics, particularly in the modeling of complex systems such as polymers and chromatin.
- 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: Detlev Borchers Triple: [Borchers, hasNotableBearer, Detlev Borchers]
Generated description
Detlev Borchers is a German journalist and writer known for his work on technology, digital culture, and media.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Detlev Borchers Target entity description: Detlev Borchers is a German journalist and writer known for his work on technology, digital culture, and media.
-
A.
Hans-Peter Kriegel
Hans-Peter Kriegel is a German computer scientist renowned for his influential contributions to data mining and database systems, particularly in clustering and similarity search.
-
B.
Rainer G. Rümmler
Rainer G. Rümmler was a German architect best known for designing numerous distinctive Berlin U-Bahn stations in the latter half of the 20th century.
-
C.
Harald Ganzinger
Harald Ganzinger was a prominent German computer scientist known for his influential work in automated theorem proving and term rewriting systems.
-
D.
Gerhard Feige
Gerhard Feige is a German Roman Catholic prelate and theologian who serves as the bishop of Magdeburg.
-
E.
Dieter W. Heermann
Dieter W. Heermann is a physicist known for his work in computational physics and biophysics, particularly in the modeling of complex systems such as polymers and chromatin.
- 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_69d8278775fc8190b0802d22ca2f495d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61b355f08190864c7322bbcb766d |
completed | April 14, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcf7f57ad88190aeb8ee0f834bfa20 |
completed | May 7, 2026, 8:37 p.m. |
| NEDg | Description generation | batch_69fcfdcbd53c81909a347e26b30f9c0b |
completed | May 7, 2026, 9:02 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fcfe9099508190bafd65d0d00129f0 |
completed | May 7, 2026, 9:05 p.m. |
Created at: April 10, 2026, 1 a.m.