Triple
T2352330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamlet (1996 film) |
E47475
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object |
Michael Maloney
Michael Maloney is a British actor known for his work in film, television, and theatre, including prominent roles in Shakespearean adaptations.
|
E329293
|
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: Michael Maloney | Statement: [Hamlet (1996 film), stars, Michael Maloney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Maloney Context triple: [Hamlet (1996 film), stars, Michael Maloney]
-
A.
Michael McCusker
Michael McCusker is an American film editor known for his work on major Hollywood productions, including the thriller "The Girl on the Train" (2016).
-
B.
Jim McKelvey
Jim McKelvey is an American entrepreneur and co-founder of the financial technology company Square (now Block, Inc.), as well as a philanthropist and author.
-
C.
Brian Mahoney
Brian Mahoney is an actor best known for his role in the cult crime film "The Boondock Saints."
-
D.
Kevin O'Connell
Kevin O'Connell is an American football coach and former NFL quarterback who serves as the head coach of the Minnesota Vikings.
-
E.
Ed McCauley
Ed McCauley is a Canadian academic and research leader who serves as president of the University of Calgary.
- 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: Michael Maloney Triple: [Hamlet (1996 film), stars, Michael Maloney]
Generated description
Michael Maloney is a British actor known for his work in film, television, and theatre, including prominent roles in Shakespearean adaptations.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michael Maloney Target entity description: Michael Maloney is a British actor known for his work in film, television, and theatre, including prominent roles in Shakespearean adaptations.
-
A.
Michael McCusker
Michael McCusker is an American film editor known for his work on major Hollywood productions, including the thriller "The Girl on the Train" (2016).
-
B.
Jim McKelvey
Jim McKelvey is an American entrepreneur and co-founder of the financial technology company Square (now Block, Inc.), as well as a philanthropist and author.
-
C.
Brian Mahoney
Brian Mahoney is an actor best known for his role in the cult crime film "The Boondock Saints."
-
D.
Kevin O'Connell
Kevin O'Connell is an American football coach and former NFL quarterback who serves as the head coach of the Minnesota Vikings.
-
E.
Ed McCauley
Ed McCauley is a Canadian academic and research leader who serves as president of the University of Calgary.
- 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_69a88a1b678c8190bce986922ba60ce0 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abc6f8ff548190b07505310e2bf0b9 |
completed | March 7, 2026, 6:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b20f1577388190bc95b2151af55732 |
completed | March 12, 2026, 12:55 a.m. |
| NEDg | Description generation | batch_69b2131c2d6081908f8586af6dcf153a |
completed | March 12, 2026, 1:13 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b213c46ca08190a1f30dccae09267d |
completed | March 12, 2026, 1:15 a.m. |
Created at: March 4, 2026, 7:54 p.m.