Triple
T18673438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hansjörg Wyss |
E456538
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Wyss |
—
|
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: Wyss | Statement: [Hansjörg Wyss, familyName, Wyss]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wyss Context triple: [Hansjörg Wyss, familyName, Wyss]
-
A.
Wyss
chosen
Wyss is a Swiss surname most notably associated with Johann David Wyss, the author of "The Swiss Family Robinson."
-
B.
Charles Weissmann
Charles Weissmann is a Swiss molecular biologist and biotechnology pioneer known for his groundbreaking work on interferons and prion diseases and for co-founding the biotech company Biogen.
-
C.
Philip Ettinger
Philip Ettinger is an American actor known for his intense, character-driven performances in film, television, and theater.
-
D.
Whitesides
Whitesides is a surname most prominently associated with George M. Whitesides, a leading American chemist and pioneer in materials science and nanotechnology.
-
E.
Peter Huber
Peter Huber is a relatively common personal name shared by multiple individuals across various professions, including law, politics, and academia.
- 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_69d8d38f72b4819090a935175d9ca8af |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e556b41cd881908f37bf7c85e96559 |
completed | April 19, 2026, 10:27 p.m. |
Created at: April 10, 2026, 11:48 a.m.