Triple
T3982585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khoe-Kwadi |
E86793
|
entity |
| Predicate | proposedBy |
P32
|
FINISHED |
| Object | Tom Güldemann |
E326613
|
NE FINISHED |
How this triple was built (2 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: Tom Güldemann | Statement: [Khoe-Kwadi, proposedBy, Tom Güldemann]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Güldemann Context triple: [Khoe-Kwadi, proposedBy, Tom Güldemann]
-
A.
Tom Güldemann
chosen
Tom Güldemann is a linguist known for his extensive research on African languages, particularly the Khoe and other Khoisan language families.
-
B.
Klaus Badelt
Klaus Badelt is a German film composer best known for his work on major Hollywood scores such as "Pirates of the Caribbean: The Curse of the Black Pearl."
-
C.
Sven Budelmann
Sven Budelmann is a German film editor known for his work on major productions including the 2022 adaptation of "All Quiet on the Western Front."
-
D.
Klaus Märtens
Klaus Märtens was a German doctor and inventor best known for creating the original air-cushioned boots that became the iconic Dr. Martens footwear brand.
-
E.
Christoph Dolle
Christoph Dolle is a German local politician who serves as the mayor of the town of Blomberg.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69aed93fd9d4819085d3b2137d2346cb |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef9dd351c81909605bc2605f541e1 |
completed | March 9, 2026, 4:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bd7f58290881908c7622616a829c75 |
completed | March 20, 2026, 5:09 p.m. |
Created at: March 9, 2026, 3:33 p.m.