Triple
T18386693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SV Darmstadt 98 |
E446610
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | Darmstadt 98 |
—
|
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: Darmstadt 98 | Statement: [SV Darmstadt 98, shortName, Darmstadt 98]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Darmstadt 98 Context triple: [SV Darmstadt 98, shortName, Darmstadt 98]
-
A.
SV Darmstadt 98
chosen
SV Darmstadt 98 is a German professional football club based in Darmstadt, best known for competing in the country’s top two leagues and its passionate local fanbase.
-
B.
Dresdner SC
Dresdner SC is a historic German sports club from Dresden, best known for its successful football team in the early 20th century.
-
C.
Hannover 96
Hannover 96 is a professional German football club based in Hanover, best known for competing in the Bundesliga and having a long history dating back to the late 19th century.
-
D.
TH Karlsruhe
TH Karlsruhe is the traditional abbreviation for the University of Karlsruhe, a prominent German technical university known for its engineering and technology programs.
-
E.
Frankfurt U9
Frankfurt U9 is a line of the Frankfurt U-Bahn rapid transit network in Frankfurt am Main, 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_69d8b9f370b88190b1e5081c2c238e7f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e517a00c608190a8f0010c7b53df90 |
completed | April 19, 2026, 5:57 p.m. |
Created at: April 10, 2026, 10:46 a.m.