Triple
T9751576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deutschland 83 |
E236453
|
entity |
| Predicate | originalNetwork |
P2594
|
FINISHED |
| Object |
RTL
RTL is a major German commercial television channel known for broadcasting popular entertainment, drama series, and reality programming.
|
E818081
|
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: RTL | Statement: [Deutschland 83, originalNetwork, RTL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RTL Context triple: [Deutschland 83, originalNetwork, RTL]
-
A.
RL
RL is the commonly used acronym for the U.S. Department of Energy’s Richland Operations Office, which oversees environmental cleanup and related activities at the Hanford Site in Washington State.
-
B.
RL
RL is an American R&B singer best known as a member of the group Next and for his smooth vocal contributions to late-1990s and early-2000s R&B hits.
-
C.
LR
LR is a German vehicle registration code assigned to the Ortenaukreis district in the state of Baden-Württemberg.
-
D.
LR
LR is the stock ticker symbol for Legrand, a global specialist in electrical and digital building infrastructure.
-
E.
LR
LR is the ISO 3166-1 alpha-2 country code for Liberia, a West African nation on the Atlantic coast.
- 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: RTL Triple: [Deutschland 83, originalNetwork, RTL]
Generated description
RTL is a major German commercial television channel known for broadcasting popular entertainment, drama series, and reality programming.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: RTL Target entity description: RTL is a major German commercial television channel known for broadcasting popular entertainment, drama series, and reality programming.
-
A.
RL
RL is the commonly used acronym for the U.S. Department of Energy’s Richland Operations Office, which oversees environmental cleanup and related activities at the Hanford Site in Washington State.
-
B.
RL
RL is an American R&B singer best known as a member of the group Next and for his smooth vocal contributions to late-1990s and early-2000s R&B hits.
-
C.
LR
LR is the stock ticker symbol for Legrand, a global specialist in electrical and digital building infrastructure.
-
D.
LR
LR is a German vehicle registration code assigned to the Ortenaukreis district in the state of Baden-Württemberg.
-
E.
LR
LR is the ISO 3166-1 alpha-2 country code for Liberia, a West African nation on the Atlantic coast.
- 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_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.