Triple
T3458875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nelonen |
E72971
|
entity |
| Predicate | sisterChannel |
P5818
|
FINISHED |
| Object |
Nelonen Pro 1
Nelonen Pro 1 is a Finnish pay television sports channel that broadcasts live coverage of various national and international sporting events.
|
E72971
|
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: Nelonen Pro 1 | Statement: [Nelonen, sisterChannel, Nelonen Pro 1]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nelonen Pro 1 Context triple: [Nelonen, sisterChannel, Nelonen Pro 1]
-
A.
Nelonen
Nelonen is a prominent Finnish commercial television channel known for broadcasting a wide range of entertainment, drama, reality shows, and sports programming.
-
B.
Noll
Noll is a surname most prominently associated with Chuck Noll, the legendary head coach who led the Pittsburgh Steelers to four Super Bowl titles.
-
C.
NARALO
NARALO is the North American Regional At-Large Organization within ICANN that represents the interests of individual internet users in the North American region.
-
D.
Nele
Nele is a Kannada novel by acclaimed Indian writer S. L. Bhyrappa, known for its philosophical depth and exploration of human values.
-
E.
NOL
NOL is the Amtrak station code for New Orleans’ main intercity rail hub, the New Orleans Union Passenger Terminal.
- 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: Nelonen Pro 1 Triple: [Nelonen, sisterChannel, Nelonen Pro 1]
Generated description
Nelonen Pro 1 is a Finnish pay television sports channel that broadcasts live coverage of various national and international sporting events.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nelonen Pro 1 Target entity description: Nelonen Pro 1 is a Finnish pay television sports channel that broadcasts live coverage of various national and international sporting events.
-
A.
Nelonen
chosen
Nelonen is a prominent Finnish commercial television channel known for broadcasting a wide range of entertainment, drama, reality shows, and sports programming.
-
B.
Noll
Noll is a surname most prominently associated with Chuck Noll, the legendary head coach who led the Pittsburgh Steelers to four Super Bowl titles.
-
C.
NARALO
NARALO is the North American Regional At-Large Organization within ICANN that represents the interests of individual internet users in the North American region.
-
D.
Nele
Nele is a Kannada novel by acclaimed Indian writer S. L. Bhyrappa, known for its philosophical depth and exploration of human values.
-
E.
NOL
NOL is the Amtrak station code for New Orleans’ main intercity rail hub, the New Orleans Union Passenger Terminal.
- 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_69ad85b12a908190a1d10a6b03b4f8ae |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbae4c18881908b48d16e46f78209 |
completed | March 8, 2026, 6:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b361093d288190a023e8485265a989 |
completed | March 13, 2026, 12:57 a.m. |
| NEDg | Description generation | batch_69b361958fd88190bd4a8d9837af6610 |
completed | March 13, 2026, 1 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b362310884819082a59ab92fe05fdd |
completed | March 13, 2026, 1:02 a.m. |
Created at: March 8, 2026, 3:16 p.m.