Triple
T8454642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karl Menger |
E199889
|
entity |
| Predicate | hasFamilyName |
P18
|
FINISHED |
| Object | Menger |
E199889
|
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: Menger | Statement: [Karl Menger, hasFamilyName, Menger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Menger Context triple: [Karl Menger, hasFamilyName, Menger]
-
A.
Menger
chosen
Menger is a surname most notably associated with Austrian mathematician Karl Menger, known for his work in topology, dimension theory, and the foundations of geometry.
-
B.
Morgenstern
Morgenstern is a German surname borne by various notable figures in fields such as economics, literature, and the arts.
-
C.
Menczel
Menczel is a variant spelling of the surname Menzel, which is of German origin and borne by various notable individuals.
-
D.
Hufstedler
Hufstedler is the surname of Shirley Hufstedler, a prominent American judge and the first U.S. Secretary of Education.
-
E.
Matzelsberger
Matzelsberger is a German-language surname most notably associated with Franziska Matzelsberger, the second wife of Emperor Franz Joseph I of Austria.
- 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_69ca8318231881908fd1bc1c4d45d286 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe48ca9988190b60ebd09a135194d |
completed | March 31, 2026, 3:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce1de232508190803fd2dad21e677f |
completed | April 2, 2026, 7:42 a.m. |
Created at: March 30, 2026, 6:10 p.m.