Triple
T3443822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karl-Heinz Weber |
E72626
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Weber |
E154323
|
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: Weber | Statement: [Karl-Heinz Weber, familyName, Weber]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Weber Context triple: [Karl-Heinz Weber, familyName, Weber]
-
A.
Weber
chosen
Weber is a common German surname borne by numerous notable individuals across fields such as sociology, music, and politics.
-
B.
Weinert
Weinert is a German-language surname borne by various notable individuals in fields such as the arts, sciences, and public life.
-
C.
Eberl
Eberl is a German-language surname of Austrian and Bavarian origin borne by various notable individuals.
-
D.
Bamberger
Bamberger is a German-origin surname notably associated with the American philanthropist and department-store co-founder Caroline Bamberger Fuld.
-
E.
Biesenthal
Biesenthal is a small town in the Barnim district of Brandenburg, Germany, known for its surrounding lakes, forests, and location within the Barnim Nature Park.
- 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_69ad85b05c848190b7a28ceec2bd7b74 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adba2a605c8190a0eafdf6f25b1e38 |
completed | March 8, 2026, 6:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b360da33e081908630e3f29ea01530 |
completed | March 13, 2026, 12:56 a.m. |
Created at: March 8, 2026, 3:16 p.m.