Triple
T23331884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ilse Lohse |
E591465
|
entity |
| Predicate | hasSurname |
P18
|
FINISHED |
| Object | Lohse |
—
|
NE NERFINISHED |
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: Lohse | Statement: [Ilse Lohse, hasSurname, Lohse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lohse Context triple: [Ilse Lohse, hasSurname, Lohse]
-
A.
Lohse
chosen
Lohse is a German surname borne by various notable individuals in fields such as science, sports, and the arts.
-
B.
Griese
Griese is a surname most prominently associated with Bob Griese, the Hall of Fame American football quarterback.
-
C.
LeRoy
LeRoy is the middle name of Marion LeRoy Burton, an American educator and university president in the early 20th century.
-
D.
LeRoy
LeRoy is the middle name of American political consultant and Republican strategist Lee Atwater.
-
E.
LeRoy
LeRoy is a masculine given name of French origin, commonly used in the United States.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e25d20156c81908c5c53195bd9c738 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f197edfbbc81908cb56507cd280737 |
completed | April 29, 2026, 5:32 a.m. |
Created at: April 17, 2026, 5:15 p.m.