Triple
T4441198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eraser |
E95773
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object |
John Kruger
John Kruger is the tough, resourceful U.S. Marshal protagonist in the 1996 action film "Eraser," portrayed by Arnold Schwarzenegger.
|
E439251
|
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: John Kruger | Statement: [Eraser, hasCharacter, John Kruger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Kruger Context triple: [Eraser, hasCharacter, John Kruger]
-
A.
Ehren Kruger
Ehren Kruger is an American screenwriter and film producer known for writing several entries in the Transformers franchise and other major Hollywood films.
-
B.
John Kamps
John Kamps is an American screenwriter best known for co-writing the family science fiction film "Zathura: A Space Adventure."
-
C.
John Kibler
John Kibler was a longtime Major League Baseball umpire best known for serving as crew chief during the 1986 World Series.
-
D.
John Schehr
John Schehr was a German communist politician and anti-fascist resistance figure who briefly led the Communist Party of Germany before being killed by the Nazis in 1934.
-
E.
John Kundla
John Kundla was a Hall of Fame American basketball coach best known for leading the Minneapolis Lakers to multiple early NBA championships.
- 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: John Kruger Triple: [Eraser, hasCharacter, John Kruger]
Generated description
John Kruger is the tough, resourceful U.S. Marshal protagonist in the 1996 action film "Eraser," portrayed by Arnold Schwarzenegger.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: John Kruger Target entity description: John Kruger is the tough, resourceful U.S. Marshal protagonist in the 1996 action film "Eraser," portrayed by Arnold Schwarzenegger.
-
A.
Ehren Kruger
Ehren Kruger is an American screenwriter and film producer known for writing several entries in the Transformers franchise and other major Hollywood films.
-
B.
John Kamps
John Kamps is an American screenwriter best known for co-writing the family science fiction film "Zathura: A Space Adventure."
-
C.
John Kibler
John Kibler was a longtime Major League Baseball umpire best known for serving as crew chief during the 1986 World Series.
-
D.
John Schehr
John Schehr was a German communist politician and anti-fascist resistance figure who briefly led the Communist Party of Germany before being killed by the Nazis in 1934.
-
E.
John Kundla
John Kundla was a Hall of Fame American basketball coach best known for leading the Minneapolis Lakers to multiple early NBA championships.
- 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_69b3453ea2b48190a26f154b3b8fece5 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b355ad71588190b1dcad4250472c29 |
completed | March 13, 2026, 12:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b61380fca08190bf036a7d82cee0e7 |
completed | March 15, 2026, 2:03 a.m. |
| NEDg | Description generation | batch_69b6143adefc81908f6c639906e0fd1a |
completed | March 15, 2026, 2:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b614b00dbc8190a7ea0477bedbc96a |
completed | March 15, 2026, 2:08 a.m. |
Created at: March 12, 2026, 11:32 p.m.