Triple
T20673573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Standing in the Spotlight |
E508098
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | German Kid |
E508098
|
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: German Kid | Statement: [Standing in the Spotlight, hasTrack, German Kid]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: German Kid Context triple: [Standing in the Spotlight, hasTrack, German Kid]
-
A.
German Kid
chosen
"German Kid" is a track from the album "Standing in the Spotlight," likely reflecting the record’s punk-influenced, offbeat musical style and themes.
-
B.
German Girl
"German Girl" is a figurative painting by British artist Euan Uglow, exemplifying his precise, measured approach to depicting the human form.
-
C.
Germann
Germann is a surname most notably associated with American actor Greg Germann, known for his roles in television and film.
-
D.
German Michel
German Michel is a national personification of the German people, typically depicted as a naive yet good-natured German everyman and often contrasted with the British figure John Bull.
-
E.
Junker
Junker is a historical noble title, particularly associated with the lower-ranking landed aristocracy in German-speaking regions, including parts of Switzerland.
- 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_69e0b4c1164881909a3bf1e3ddb2bc32 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b5cca8808190a60ee28c7ea46412 |
completed | April 20, 2026, 11:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08d7da54588190b0f13d8b4d6d4d51 |
completed | May 16, 2026, 8:47 p.m. |
Created at: April 16, 2026, 11:44 a.m.