Triple
T19592396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Straße des 17. Juni |
E470267
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Großer Stern |
—
|
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: Großer Stern | Statement: [Straße des 17. Juni, passesThrough, Großer Stern]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Großer Stern Context triple: [Straße des 17. Juni, passesThrough, Großer Stern]
-
A.
Großer Stern
chosen
Großer Stern is a major traffic roundabout and central junction in Berlin’s Tiergarten park, known for hosting the city’s Victory Column at its center.
-
B.
Südstern
Südstern is a Berlin U-Bahn station on line U7 located in the Kreuzberg district.
-
C.
Kinderstern
Kinderstern is a well-known abstract artwork by German artist Imi Knoebel, characterized by its minimalist star motif and bold use of color.
-
D.
The Star
The Star is a 1952 drama film starring Bette Davis as a fading Hollywood actress struggling with the loss of her fame and career.
-
E.
The Star
The Star was a late 19th-century London evening newspaper known for its sensational and often moralistic coverage of crime and scandal.
- 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_69d8e510024481908415c0d616fa6186 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e64057460c8190962e2e58f06b3985 |
completed | April 20, 2026, 3:03 p.m. |
Created at: April 10, 2026, 1:43 p.m.