Triple
T11049776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maniac (2012 film) |
E261214
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Megan Duffy
Megan Duffy is an American actress and producer best known for her work in independent horror films and genre television.
|
E952122
|
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: Megan Duffy | Statement: [Maniac (2012 film), starring, Megan Duffy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Megan Duffy Context triple: [Maniac (2012 film), starring, Megan Duffy]
-
A.
Megan Walsh
Megan Walsh is the teenage government-trained assassin who goes undercover as a high school student in the action-comedy film "Barely Lethal."
-
B.
Megan Ferguson
Megan Ferguson is an American actress known for her work in television comedies and dramas, including a prominent role in the series "The Comedians."
-
C.
Megan McArthur
Megan McArthur is a NASA astronaut and oceanographer best known for her role as a mission specialist on Space Shuttle missions, including the final Hubble Space Telescope servicing flight.
-
D.
Megan Morgan
Megan Morgan is a character from the 1988 sci-fi horror comedy film "Critters 2: The Main Course."
-
E.
Meghan McDermott
Meghan McDermott is an American public relations and communications professional best known for her marriage to actor Theo Rossi.
- 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: Megan Duffy Triple: [Maniac (2012 film), starring, Megan Duffy]
Generated description
Megan Duffy is an American actress and producer best known for her work in independent horror films and genre television.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Megan Duffy Target entity description: Megan Duffy is an American actress and producer best known for her work in independent horror films and genre television.
-
A.
Megan Walsh
Megan Walsh is the teenage government-trained assassin who goes undercover as a high school student in the action-comedy film "Barely Lethal."
-
B.
Megan Ferguson
Megan Ferguson is an American actress known for her work in television comedies and dramas, including a prominent role in the series "The Comedians."
-
C.
Megan McArthur
Megan McArthur is a NASA astronaut and oceanographer best known for her role as a mission specialist on Space Shuttle missions, including the final Hubble Space Telescope servicing flight.
-
D.
Megan Morgan
Megan Morgan is a character from the 1988 sci-fi horror comedy film "Critters 2: The Main Course."
-
E.
Meghan McDermott
Meghan McDermott is an American public relations and communications professional best known for her marriage to actor Theo Rossi.
- 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_69d6aa98650481908609c7c56bfa7902 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79868c78881908c8e3672c05ae7ec |
completed | April 9, 2026, 12:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f28053fe08819099e848cd74b989a0 |
completed | April 29, 2026, 10:04 p.m. |
| NEDg | Description generation | batch_69f40b2d0a388190a11a0e2d806e310b |
completed | May 1, 2026, 2:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f40deb4eec8190a8fe1aa59b1514e6 |
completed | May 1, 2026, 2:20 a.m. |
Created at: April 8, 2026, 9:26 p.m.