Triple
T16214474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weißensee |
E393549
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object |
Kino Toni
Kino Toni is a historic neighborhood cinema in Berlin’s Weißensee district, known for its local charm and cultural significance.
|
E1200240
|
NE FINISHED |
How this triple was built (4 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: Kino Toni | Statement: [Weißensee, hasLandmark, Kino Toni]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kino Toni Context triple: [Weißensee, hasLandmark, Kino Toni]
-
A.
Kino
Kino is the impoverished Mexican-Indian pearl diver and tragic protagonist of John Steinbeck’s novella "The Pearl."
-
B.
Kino Loy
Kino Loy is a character in the Star Wars series "Andor," known as a hardened yet principled inmate who becomes a key leader in the Narkina 5 prison uprising.
-
C.
Jino
Jino are an officially recognized ethnic minority group in China, primarily living in Yunnan Province and known for their distinct language and traditional culture.
-
D.
Munchi
Munchi is an alternative name for the Tiv language, a Southern Bantoid language spoken primarily in central Nigeria.
-
E.
Munchi
Munchi is a Dutch music producer and DJ known for pioneering the modern moombahton sound by blending reggaeton, house, and various global bass influences.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kino Toni Triple: [Weißensee, hasLandmark, Kino Toni]
Generated description
Kino Toni is a historic neighborhood cinema in Berlin’s Weißensee district, known for its local charm and cultural significance.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kino Toni Target entity description: Kino Toni is a historic neighborhood cinema in Berlin’s Weißensee district, known for its local charm and cultural significance.
-
A.
Kino
Kino is the impoverished Mexican-Indian pearl diver and tragic protagonist of John Steinbeck’s novella "The Pearl."
-
B.
Kino Loy
Kino Loy is a character in the Star Wars series "Andor," known as a hardened yet principled inmate who becomes a key leader in the Narkina 5 prison uprising.
-
C.
Jino
Jino are an officially recognized ethnic minority group in China, primarily living in Yunnan Province and known for their distinct language and traditional culture.
-
D.
Munchi
Munchi is an alternative name for the Tiv language, a Southern Bantoid language spoken primarily in central Nigeria.
-
E.
Munchi
Munchi is a Dutch music producer and DJ known for pioneering the modern moombahton sound by blending reggaeton, house, and various global bass influences.
- F. None of above. chosen
Provenance (5 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_69d87f1f5bd08190bd01cac0d5b9d2ef |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e227f393e08190be93400d754f0a2d |
completed | April 17, 2026, 12:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a000794e6c881909c4521e4dd031971 |
completed | May 10, 2026, 4:20 a.m. |
| NEDg | Description generation | batch_6a00084d8e308190bd90811392586753 |
completed | May 10, 2026, 4:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0008c7430c81908b9620369c609ad8 |
completed | May 10, 2026, 4:25 a.m. |
Created at: April 10, 2026, 5:03 a.m.