Triple
T8482973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rainbow DQN |
E200562
|
entity |
| Predicate | proposedBy |
P32
|
FINISHED |
| Object | Tom Schaul |
E512320
|
NE FINISHED |
How this triple was built (2 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: Tom Schaul | Statement: [Rainbow DQN, proposedBy, Tom Schaul]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Schaul Context triple: [Rainbow DQN, proposedBy, Tom Schaul]
-
A.
Tom Schaul
chosen
Tom Schaul is a machine learning researcher known for his contributions to deep reinforcement learning, including co-developing the Dueling DQN architecture.
-
B.
Alan Schilke
Alan Schilke is a prominent roller coaster engineer known for designing innovative and extreme thrill rides for major amusement parks worldwide.
-
C.
Fred Schuler
Fred Schuler is a cinematographer best known for his work on films such as the 1980 comedy "Stir Crazy."
-
D.
Guy Schuessler
Guy Schuessler is a British actor and theatre professional best known as the husband of acclaimed stage and screen actress Dame Harriet Walter.
-
E.
Jerry Schatz
Jerry Schatz is an individual notable enough to be recognized as a namesake of the surname Schatz.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca831b17988190a1f3f3413d57b820 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe53845e881909eeb32863c7aa942 |
completed | March 31, 2026, 3:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cea83707e481909f9dfd6450a28d3d |
completed | April 2, 2026, 5:32 p.m. |
Created at: March 30, 2026, 6:12 p.m.