Triple
T3621598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Megamind |
E76738
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Hal Stewart
Hal Stewart is the cameraman-turned-supervillain known as Tighten in the animated film "Megamind."
|
E380939
|
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: Hal Stewart | Statement: [Megamind, mainCharacter, Hal Stewart]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hal Stewart Context triple: [Megamind, mainCharacter, Hal Stewart]
-
A.
Roy Stewart
Roy Stewart was an American silent film actor known for his roles in early Westerns and adventure films during the 1910s and 1920s.
-
B.
Richard Stolley
Richard Stolley was an influential American magazine editor best known for shaping modern celebrity journalism as the founding managing editor of People magazine.
-
C.
Jim Hutton
Jim Hutton was an American actor best known for his lanky, affable screen presence in 1960s comedies and for playing the title role in the TV series "Ellery Queen."
-
D.
Ray Cusick
Ray Cusick was a British designer best known for creating the iconic look of the Daleks in the long-running science fiction television series Doctor Who.
-
E.
Tim Stevenson
Tim Stevenson is a British public servant who has served as the ceremonial representative of the monarch in Oxfordshire.
- 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: Hal Stewart Triple: [Megamind, mainCharacter, Hal Stewart]
Generated description
Hal Stewart is the cameraman-turned-supervillain known as Tighten in the animated film "Megamind."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hal Stewart Target entity description: Hal Stewart is the cameraman-turned-supervillain known as Tighten in the animated film "Megamind."
-
A.
Roy Stewart
Roy Stewart was an American silent film actor known for his roles in early Westerns and adventure films during the 1910s and 1920s.
-
B.
Richard Stolley
Richard Stolley was an influential American magazine editor best known for shaping modern celebrity journalism as the founding managing editor of People magazine.
-
C.
Jim Hutton
Jim Hutton was an American actor best known for his lanky, affable screen presence in 1960s comedies and for playing the title role in the TV series "Ellery Queen."
-
D.
Ray Cusick
Ray Cusick was a British designer best known for creating the iconic look of the Daleks in the long-running science fiction television series Doctor Who.
-
E.
Tim Stevenson
Tim Stevenson is a British public servant who has served as the ceremonial representative of the monarch in Oxfordshire.
- 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_69ad85dae2fc81908d1ceadbc6af0089 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc2bb12cc8190bd67597cf3b66a3a |
completed | March 8, 2026, 6:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4c3852e60819092db2992e945a4c7 |
completed | March 14, 2026, 2:10 a.m. |
| NEDg | Description generation | batch_69b4c7f0fe1c8190b66e3fcecfae3f6e |
completed | March 14, 2026, 2:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4c840713c81908e3d565d663e04d5 |
completed | March 14, 2026, 2:30 a.m. |
Created at: March 8, 2026, 3:23 p.m.