Triple
T20323826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Risch |
E492280
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Risch |
—
|
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: Risch | Statement: [Daniel Risch, familyName, Risch]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Risch Context triple: [Daniel Risch, familyName, Risch]
-
A.
Risch
chosen
Risch is a Swiss municipality in the canton of Zug, known for its lakeside location and residential communities along Lake Zug.
-
B.
Raschi
Raschi is an Italian surname most notably associated with Vic Raschi, a star pitcher for the New York Yankees in the late 1940s and early 1950s.
-
C.
Rubi
Rubi is a popular Arabic-language television drama series that helped boost Egyptian actor Amr Waked’s regional fame.
-
D.
Zippel
Zippel is a surname most notably associated with American lyricist and songwriter David Zippel.
-
E.
Ris
Ris is a residential neighborhood in Oslo, Norway, known for its leafy streets, proximity to nature, and access via the Holmenkollen Line.
- 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_69e0b4a0134081909113563e1c3ba68a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6778e59508190bfd7a3ce44d56a93 |
completed | April 20, 2026, 6:59 p.m. |
Created at: April 16, 2026, 11:21 a.m.