Triple
T6391662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malcolm H. Wiener |
E143841
|
entity |
| Predicate | hasFamilyName |
P18
|
FINISHED |
| Object | Wiener |
E158216
|
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: Wiener | Statement: [Malcolm H. Wiener, hasFamilyName, Wiener]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wiener Context triple: [Malcolm H. Wiener, hasFamilyName, Wiener]
-
A.
Wiener
chosen
Wiener is a surname most notably associated with Norbert Wiener, the American mathematician and founder of cybernetics.
-
B.
Berliner
Berliner is a German-origin surname most notably associated with Emile Berliner, the inventor of the gramophone and a pioneer in sound recording technology.
-
C.
Bamberger
Bamberger is a German-origin surname notably associated with the American philanthropist and department-store co-founder Caroline Bamberger Fuld.
-
D.
Heunisch Weiss
Heunisch Weiss is an ancient European white grape variety historically important as a parent of many classic wine grapes, including Chardonnay and Riesling.
-
E.
Oberkrämer
Oberkrämer is a rural municipality in the Oberhavel district of Brandenburg, Germany, known for its villages, agricultural landscape, and proximity to Berlin.
- 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_69c008db906c819096f3597d55d95432 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0687db4b881909dd84d5a947cc3e3 |
completed | March 22, 2026, 10:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6388b02888190989623c658469a5a |
completed | March 27, 2026, 7:58 a.m. |
Created at: March 22, 2026, 4:34 p.m.