Triple
T2722882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jürgen Klopp |
E60121
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Jürgen |
E140183
|
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: Jürgen | Statement: [Jürgen Klopp, givenName, Jürgen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jürgen Context triple: [Jürgen Klopp, givenName, Jürgen]
-
A.
Jürgen
chosen
Jürgen is a masculine given name of German origin, commonly used in German-speaking countries.
-
B.
Helmut
Helmut is a masculine given name of German origin, historically common in German-speaking countries.
-
C.
Hans-Jürgen
Hans-Jürgen is a masculine German given name, typically used as a compound first name combining "Hans" and "Jürgen."
-
D.
Erich
Erich is a masculine given name of German origin, commonly used in German-speaking countries and beyond.
-
E.
Olaf Kölzig
Olaf Kölzig is a former German-Canadian NHL goaltender best known for his long, standout career with the Washington Capitals, including winning the Vezina Trophy in 2000.
- 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_69ab4b746d248190958e052045c09255 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdab2f36c8190aa0b452e57525fe0 |
completed | March 7, 2026, 7:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afb6939a50819087ac2c55337ceae3 |
completed | March 10, 2026, 6:13 a.m. |
Created at: March 6, 2026, 9:55 p.m.