Triple
T3757790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Wackness |
E82088
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Aaron Yoo
Aaron Yoo is an American actor known for his supporting roles in films like "Disturbia," "21," and "Nick and Norah's Infinite Playlist," as well as various television appearances.
|
E385694
|
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: Aaron Yoo | Statement: [The Wackness, starring, Aaron Yoo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aaron Yoo Context triple: [The Wackness, starring, Aaron Yoo]
-
A.
Greg Yang
Greg Yang is a mathematician and AI researcher known for his work on the theoretical foundations of deep learning and his role at xAI.
-
B.
Ken Kao
Ken Kao is an American film producer known for backing a range of independent and auteur-driven projects.
-
C.
Christopher Chung
Christopher Chung is an actor known for his role in the British spy drama series "Slow Horses."
-
D.
David Luan
David Luan is an AI researcher and entrepreneur known for his work on large language models at OpenAI and as co-founder and CEO of Adept AI.
-
E.
Jun-Ho Oh
Jun-Ho Oh is a South Korean roboticist best known for leading the development of the humanoid robot DRC-HUBO that won the DARPA Robotics Challenge.
- 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: Aaron Yoo Triple: [The Wackness, starring, Aaron Yoo]
Generated description
Aaron Yoo is an American actor known for his supporting roles in films like "Disturbia," "21," and "Nick and Norah's Infinite Playlist," as well as various television appearances.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Aaron Yoo Target entity description: Aaron Yoo is an American actor known for his supporting roles in films like "Disturbia," "21," and "Nick and Norah's Infinite Playlist," as well as various television appearances.
-
A.
Greg Yang
Greg Yang is a mathematician and AI researcher known for his work on the theoretical foundations of deep learning and his role at xAI.
-
B.
Ken Kao
Ken Kao is an American film producer known for backing a range of independent and auteur-driven projects.
-
C.
Christopher Chung
Christopher Chung is an actor known for his role in the British spy drama series "Slow Horses."
-
D.
David Luan
David Luan is an AI researcher and entrepreneur known for his work on large language models at OpenAI and as co-founder and CEO of Adept AI.
-
E.
Jun-Ho Oh
Jun-Ho Oh is a South Korean roboticist best known for leading the development of the humanoid robot DRC-HUBO that won the DARPA Robotics Challenge.
- 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_69ad8b1db40081908b61ffa6b78afd4d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcbc04d348190b0e4a90d18bdd160 |
completed | March 8, 2026, 7:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4e50f77fc8190b7774a7359118c9c |
completed | March 14, 2026, 4:33 a.m. |
| NEDg | Description generation | batch_69b4e5fe22f0819088effd8a0eae72e6 |
completed | March 14, 2026, 4:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4e671e02c819094cae2a3a2abb1b4 |
completed | March 14, 2026, 4:39 a.m. |
Created at: March 8, 2026, 3:35 p.m.