Triple
T9751624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deutschland 86 |
E236454
|
entity |
| Predicate | producedBy |
P490
|
FINISHED |
| Object |
UFA Fiction
UFA Fiction is a German television and film production company known for creating high-profile scripted series and dramas.
|
E355973
|
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: UFA Fiction | Statement: [Deutschland 86, producedBy, UFA Fiction]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: UFA Fiction Context triple: [Deutschland 86, producedBy, UFA Fiction]
-
A.
FIC
FIC is the acronym for the Fogarty International Center, a division of the U.S. National Institutes of Health that supports global health research and training.
-
B.
Fiction & Cie
Fiction & Cie is a literary imprint known for publishing innovative and contemporary fiction under the French publishing house Éditions du Seuil.
-
C.
UFA
UFA (Universum Film AG) was a major German film production and distribution company, especially prominent during the Weimar Republic and early 20th-century cinema.
-
D.
UFA
UFA is the acronym for the Uniformed Firefighters Association, the labor union representing New York City’s rank-and-file firefighters.
-
E.
USFF
USFF is the acronym for U.S. Fleet Forces Command, the major U.S. Navy command responsible for organizing, training, and equipping naval forces for deployment.
- 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: UFA Fiction Triple: [Deutschland 86, producedBy, UFA Fiction]
Generated description
UFA Fiction is a German television and film production company known for creating high-profile scripted series and dramas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: UFA Fiction Target entity description: UFA Fiction is a German television and film production company known for creating high-profile scripted series and dramas.
-
A.
FIC
FIC is the acronym for the Fogarty International Center, a division of the U.S. National Institutes of Health that supports global health research and training.
-
B.
Fiction & Cie
Fiction & Cie is a literary imprint known for publishing innovative and contemporary fiction under the French publishing house Éditions du Seuil.
-
C.
UFA
chosen
UFA (Universum Film AG) was a major German film production and distribution company, especially prominent during the Weimar Republic and early 20th-century cinema.
-
D.
UFA
UFA is the acronym for the Uniformed Firefighters Association, the labor union representing New York City’s rank-and-file firefighters.
-
E.
USFF
USFF is the acronym for U.S. Fleet Forces Command, the major U.S. Navy command responsible for organizing, training, and equipping naval forces for deployment.
- F. None of above.
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_69ca84d4eddc8190996fec1417d2bae8 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9facd5b881909f0569b23f308815 |
completed | April 1, 2026, 10:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1b020829481908456e7977c5f9adb |
completed | April 5, 2026, 12:43 a.m. |
| NEDg | Description generation | batch_69d1b0dde93881908fcec28de9cfa99d |
completed | April 5, 2026, 12:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1b1bbe6108190af17b75f79c0f465 |
completed | April 5, 2026, 12:50 a.m. |
Created at: March 30, 2026, 8:24 p.m.