Triple
T4461343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wigner–Eckart theorem |
E98261
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Carl Eckart |
E362435
|
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: Carl Eckart | Statement: [Wigner–Eckart theorem, namedAfter, Carl Eckart]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carl Eckart Context triple: [Wigner–Eckart theorem, namedAfter, Carl Eckart]
-
A.
Carl Eckart
chosen
Carl Eckart was an American physicist and applied mathematician known for his contributions to quantum mechanics, fluid dynamics, and the development of the Wigner–Eckart theorem.
-
B.
Carl Spitz
Carl Spitz was a renowned German-American dog trainer best known for training Toto in the classic film "The Wizard of Oz."
-
C.
Karl Schaefer
Karl Schaefer is a television writer and producer best known for co-creating the zombie apocalypse series Z Nation and its Netflix prequel Black Summer.
-
D.
Rudolf Garrels
Rudolf Garrels was an 18th-century Dutch organ builder known for constructing and maintaining notable church organs in the Netherlands.
-
E.
Gustave Herter
Gustave Herter was a prominent 19th-century German-born American cabinetmaker and interior designer known for his luxurious, highly detailed work for elite clients and landmark buildings in the United States.
- 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_69b3454a7c608190944f5455c8031d73 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35674f718819089388c3924dd1414 |
completed | March 13, 2026, 12:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6284b90708190b557b66bd7533f4e |
completed | March 15, 2026, 3:32 a.m. |
Created at: March 12, 2026, 11:34 p.m.