Triple
T23027807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jürgen Thiel |
E573368
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Jürgen |
—
|
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: Jürgen | Statement: [Jürgen Thiel, givenName, Jürgen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jürgen Context triple: [Jürgen Thiel, givenName, Jürgen]
-
A.
Jürgen
chosen
Jürgen is a masculine given name of German origin, commonly used in German-speaking countries.
-
B.
Jörg
Jörg is a masculine given name of German origin, commonly used in German-speaking countries.
-
C.
Rüdiger
Rüdiger is a German given name of Germanic origin, commonly used as a masculine first name in German-speaking countries.
-
D.
Rudi Jäger
Rudi Jäger is a sadistic Nazi prison warden and antagonist in the video game Wolfenstein: The Old Blood, known for hunting the protagonist with his attack dogs.
-
E.
Holger Meins
Holger Meins was a German cinematography student and militant who became a prominent member of the Red Army Faction and died on hunger strike in prison, turning into a symbol for parts of the radical left in 1970s West Germany.
- 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_69e245b821008190b0e09cb02092aae1 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1847e48c48190894525c354663dd2 |
completed | April 29, 2026, 4:09 a.m. |
Created at: April 17, 2026, 3:52 p.m.