Triple
T6725094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mike Richter |
E153496
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Richter |
E228360
|
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: Richter | Statement: [Mike Richter, familyName, Richter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Richter Context triple: [Mike Richter, familyName, Richter]
-
A.
Richter
chosen
Richter is a common German surname borne by numerous notable individuals, including artists, scientists, and public figures.
-
B.
Rikter Bedan
Rikter Bedan is a notable literary work by Bengali poet and revolutionary Kazi Nazrul Islam, reflecting his characteristic themes of rebellion and humanism.
-
C.
Morgenstern
Morgenstern is a German surname borne by various notable figures in fields such as economics, literature, and the arts.
-
D.
Stahlecker
Stahlecker is a German-language surname most notably associated with Franz Walter Stahlecker, a high-ranking SS officer and Nazi official during World War II.
-
E.
Riß
The Riß is a river in the German state of Baden-Württemberg that flows through the Alb-Donau district before joining the Danube.
- 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_69c6880afb988190ad88011b48ecfcba |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d14fb1a8819083287ca8bb576bba |
completed | March 27, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c700a34e248190ba9d73437b19a96d |
completed | March 27, 2026, 10:11 p.m. |
Created at: March 27, 2026, 2:08 p.m.