Triple
T21993441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goede tijden, slechte tijden |
E543144
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object |
Tim Loderus
Tim Loderus is a fictional character from the long-running Dutch soap opera "Goede tijden, slechte tijden."
|
E1512518
|
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: Tim Loderus | Statement: [Goede tijden, slechte tijden, hasCharacter, Tim Loderus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tim Loderus Context triple: [Goede tijden, slechte tijden, hasCharacter, Tim Loderus]
-
A.
Ryan Lomberg
Ryan Lomberg is a Canadian professional ice hockey forward known for his energetic, physical style of play in the NHL.
-
B.
Steve Lombard
Steve Lombard is a fictional sports editor and former football star in DC Comics, best known as a brash, prank-loving colleague of Clark Kent at the Daily Planet.
-
C.
Phil Leotardo
Phil Leotardo is a ruthless New York mob boss and major antagonist in the television series "The Sopranos."
-
D.
Larry Lovestein
Larry Lovestein is an alternate musical persona of rapper and producer Mac Miller, used primarily for his jazz-influenced, lounge-style projects.
-
E.
Leon Fromkess
Leon Fromkess was an American film producer active during Hollywood’s studio era, known for overseeing a variety of mid-20th-century motion pictures.
- 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: Tim Loderus Triple: [Goede tijden, slechte tijden, hasCharacter, Tim Loderus]
Generated description
Tim Loderus is a fictional character from the long-running Dutch soap opera "Goede tijden, slechte tijden."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tim Loderus Target entity description: Tim Loderus is a fictional character from the long-running Dutch soap opera "Goede tijden, slechte tijden."
-
A.
Ryan Lomberg
Ryan Lomberg is a Canadian professional ice hockey forward known for his energetic, physical style of play in the NHL.
-
B.
Steve Lombard
Steve Lombard is a fictional sports editor and former football star in DC Comics, best known as a brash, prank-loving colleague of Clark Kent at the Daily Planet.
-
C.
Phil Leotardo
Phil Leotardo is a ruthless New York mob boss and major antagonist in the television series "The Sopranos."
-
D.
Larry Lovestein
Larry Lovestein is an alternate musical persona of rapper and producer Mac Miller, used primarily for his jazz-influenced, lounge-style projects.
-
E.
Leon Fromkess
Leon Fromkess was an American film producer active during Hollywood’s studio era, known for overseeing a variety of mid-20th-century motion pictures.
- 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_69e11e2c814c8190837d072789000486 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1270f77fc8190aadcc02760d65ac0 |
completed | April 28, 2026, 9:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a6d85f104819088dba8d0bf347fbe |
completed | May 18, 2026, 1:38 a.m. |
| NEDg | Description generation | batch_6a0a6e556f3c8190927d1c0cba23463c |
completed | May 18, 2026, 1:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a6f3de2e88190824c9cc266c7ee8c |
completed | May 18, 2026, 1:45 a.m. |
Created at: April 16, 2026, 8:17 p.m.