Triple
T6985731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Herzog |
E161955
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | Roman Herzog |
E30668
|
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: Roman Herzog | Statement: [Herzog, hasNotableBearer, Roman Herzog]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roman Herzog Context triple: [Herzog, hasNotableBearer, Roman Herzog]
-
A.
Roman Herzog
chosen
Roman Herzog was a German jurist and politician who served as President of Germany from 1994 to 1999.
-
B.
Andreas von Weizsäcker
Andreas von Weizsäcker was a German sculptor and member of the prominent von Weizsäcker family.
-
C.
Siegfried Kohl
Siegfried Kohl is an individual notable for bearing the German surname "Kohl," which is associated with several prominent figures.
-
D.
Ernst von Weizsäcker
Ernst von Weizsäcker was a German diplomat who served as State Secretary in the Foreign Office under the Nazi regime and was later convicted for his role in its policies at the post-World War II Ministries Trial.
-
E.
Fritz von Weizsäcker
Fritz von Weizsäcker was a German physician and professor of internal medicine who served as chief physician at Berlin’s Schlosspark-Klinik and was tragically killed during a public lecture in 2019.
- 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_69c68855dc0481909b4c7e9e9ed273db |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6db93c0ac8190a752a633247bb439 |
completed | March 27, 2026, 7:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7883f0d988190b170901aea57d360 |
completed | March 28, 2026, 7:50 a.m. |
Created at: March 27, 2026, 2:31 p.m.