Triple
T10282321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donald Kushner |
E241131
|
entity |
| Predicate | producerOf |
P490
|
FINISHED |
| Object |
Monster
Monster is a 2003 biographical crime drama film about serial killer Aileen Wuornos, starring Charlize Theron in an Oscar-winning performance.
|
E50475
|
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: Monster | Statement: [Donald Kushner, producerOf, Monster]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Monster Context triple: [Donald Kushner, producerOf, Monster]
-
A.
Monster
Monster is a 2003 biographical crime drama film in which Charlize Theron delivers an Oscar-winning performance as serial killer Aileen Wuornos.
-
B.
Monster
Monster is a town in the Dutch province of South Holland, known for its coastal location near the North Sea and its greenhouse horticulture.
-
C.
Monster
"Monster" is a standout track from Kanye West’s critically acclaimed album *My Beautiful Dark Twisted Fantasy*, known for its high-profile guest verses and dark, aggressive themes.
-
D.
Monster
Monster is a popular energy drink brand known for its high-caffeine beverages and aggressive, extreme-sports-oriented marketing.
-
E.
Monster
"Monster" is a critically acclaimed Japanese manga series by Naoki Urasawa, known for its dark psychological thriller narrative about a doctor entangled with a serial killer.
- 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: Monster Triple: [Donald Kushner, producerOf, Monster]
Generated description
Monster is a 2003 biographical crime drama film about serial killer Aileen Wuornos, starring Charlize Theron in an Oscar-winning performance.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Monster Target entity description: Monster is a 2003 biographical crime drama film about serial killer Aileen Wuornos, starring Charlize Theron in an Oscar-winning performance.
-
A.
Monster
chosen
Monster is a 2003 biographical crime drama film in which Charlize Theron delivers an Oscar-winning performance as serial killer Aileen Wuornos.
-
B.
Monster
Monster is a town in the Dutch province of South Holland, known for its coastal location near the North Sea and its greenhouse horticulture.
-
C.
Monster
"Monster" is a standout track from Kanye West’s critically acclaimed album *My Beautiful Dark Twisted Fantasy*, known for its high-profile guest verses and dark, aggressive themes.
-
D.
Monster
Monster is a popular energy drink brand known for its high-caffeine beverages and aggressive, extreme-sports-oriented marketing.
-
E.
Monster
"Monster" is a critically acclaimed Japanese manga series by Naoki Urasawa, known for its dark psychological thriller narrative about a doctor entangled with a serial killer.
- 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_69d381a94c1881908fc38fc263d9b9c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2a177b48190aab7d7857f5bba7b |
completed | April 7, 2026, 9:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f8352a108190b3692a2de3cb4dea |
completed | April 9, 2026, 12:52 a.m. |
| NEDg | Description generation | batch_69d6fcae243c819095a2e791716805bd |
completed | April 9, 2026, 1:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d6fd3495fc8190a093d2536cfbe58a |
completed | April 9, 2026, 1:13 a.m. |
Created at: April 6, 2026, 11:39 a.m.