Triple
T6330028
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Shannon |
E141954
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
The Iceman
The Iceman is a 2012 crime thriller film in which Michael Shannon portrays real-life contract killer Richard Kuklinski.
|
E585584
|
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: The Iceman | Statement: [Michael Shannon, notableWork, The Iceman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Iceman Context triple: [Michael Shannon, notableWork, The Iceman]
-
A.
The Iceman
The Iceman is the Hall of Fame NBA shooting guard George Gervin, renowned for his smooth scoring ability and signature finger roll.
-
B.
The Iceman
The Iceman is the nickname of Dutch football legend Dennis Bergkamp, renowned for his composure, elegance, and technical brilliance on the pitch.
-
C.
Iceman
Iceman is the nickname of Adam Vinatieri, the legendary NFL placekicker renowned for his clutch, game-winning field goals under extreme pressure.
-
D.
Iceman
Iceman is a founding member of the X-Men with the mutant ability to generate and control ice and cold.
-
E.
“The Grauballe Man”
The Grauballe Man is a remarkably well-preserved Iron Age bog body discovered in Denmark, notable for the insights it provides into ancient ritual practices and everyday life.
- 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: The Iceman Triple: [Michael Shannon, notableWork, The Iceman]
Generated description
The Iceman is a 2012 crime thriller film in which Michael Shannon portrays real-life contract killer Richard Kuklinski.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: The Iceman Target entity description: The Iceman is a 2012 crime thriller film in which Michael Shannon portrays real-life contract killer Richard Kuklinski.
-
A.
The Iceman
The Iceman is the Hall of Fame NBA shooting guard George Gervin, renowned for his smooth scoring ability and signature finger roll.
-
B.
The Iceman
The Iceman is the nickname of Dutch football legend Dennis Bergkamp, renowned for his composure, elegance, and technical brilliance on the pitch.
-
C.
Iceman
Iceman is the nickname of Adam Vinatieri, the legendary NFL placekicker renowned for his clutch, game-winning field goals under extreme pressure.
-
D.
Iceman
Iceman is a founding member of the X-Men with the mutant ability to generate and control ice and cold.
-
E.
“The Grauballe Man”
The Grauballe Man is a remarkably well-preserved Iron Age bog body discovered in Denmark, notable for the insights it provides into ancient ritual practices and everyday life.
- 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_69c008d201748190917e69c41ba3f978 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0651334c08190a9514faa36e7812d |
completed | March 22, 2026, 9:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6041aac948190ad7dd4d5683903ed |
completed | March 27, 2026, 4:14 a.m. |
| NEDg | Description generation | batch_69c6053eb344819094490ad663413962 |
completed | March 27, 2026, 4:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c605d48e848190bf11f3862a12d709 |
completed | March 27, 2026, 4:21 a.m. |
Created at: March 22, 2026, 4:30 p.m.