Triple
T18084185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tino Gross |
E432789
|
entity |
| Predicate | knownAs |
P39
|
FINISHED |
| Object | Tino Gross |
—
|
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: Tino Gross | Statement: [Tino Gross, knownAs, Tino Gross]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tino Gross Context triple: [Tino Gross, knownAs, Tino Gross]
-
A.
Tino Gross
chosen
Tino Gross is a musician best known as a member of Kid Rock’s backing band, Twisted Brown Trucker.
-
B.
Leon Kochnitzky
Leon Kochnitzky was a Belgian intellectual and political activist known for his involvement with Gabriele D’Annunzio’s nationalist Fiume enterprise after World War I.
-
C.
Matthias Grunsky
Matthias Grunsky is an Austrian cinematographer known for his long-time collaboration with director Andrew Bujalski on acclaimed independent films.
-
D.
Rico Badenschier
Rico Badenschier is a German politician who serves as the mayor of the city of Schwerin.
-
E.
Marco Streller
Marco Streller is a retired Swiss footballer and prolific striker best known for his successful spells with FC Basel and appearances for the Swiss national team.
- 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_69d8b907d05c819083cc3bd6021089e6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4d9fcdbec819085752e7605ae7772 |
completed | April 19, 2026, 1:34 p.m. |
Created at: April 10, 2026, 10:27 a.m.