Triple
T13208621
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Madsen |
E314429
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Madsen
Madsen is a Danish-origin surname borne by various notable individuals across fields such as acting, sports, and politics.
|
E1027431
|
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: Madsen | Statement: [Michael Madsen, familyName, Madsen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Madsen Context triple: [Michael Madsen, familyName, Madsen]
-
A.
Bushmaster
The Bushmaster is a heavily armored, mine-resistant infantry mobility vehicle widely used for troop transport and protection in modern military operations.
-
B.
Bushmaster
Bushmaster is a superpowered crime boss and martial artist in Marvel Comics, best known as a formidable adversary of Luke Cage.
-
C.
Speer
Speer is a German surname most famously associated with Albert Speer, the Nazi architect and Minister of Armaments and War Production during World War II.
-
D.
Diemaco
Diemaco is a Canadian firearms manufacturer best known for producing and developing variants of the AR-15/M16 family of rifles for military and law enforcement use.
-
E.
Colt 45
Colt 45 is a French crime thriller film centered on a talented young police armorer drawn into a violent underworld of corruption and gun trafficking.
- 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: Madsen Triple: [Michael Madsen, familyName, Madsen]
Generated description
Madsen is a Danish-origin surname borne by various notable individuals across fields such as acting, sports, and politics.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Madsen Target entity description: Madsen is a Danish-origin surname borne by various notable individuals across fields such as acting, sports, and politics.
-
A.
Bushmaster
The Bushmaster is a heavily armored, mine-resistant infantry mobility vehicle widely used for troop transport and protection in modern military operations.
-
B.
Bushmaster
Bushmaster is a superpowered crime boss and martial artist in Marvel Comics, best known as a formidable adversary of Luke Cage.
-
C.
Speer
Speer is a German surname most famously associated with Albert Speer, the Nazi architect and Minister of Armaments and War Production during World War II.
-
D.
Diemaco
Diemaco is a Canadian firearms manufacturer best known for producing and developing variants of the AR-15/M16 family of rifles for military and law enforcement use.
-
E.
Colt 45
Colt 45 is a French crime thriller film centered on a talented young police armorer drawn into a violent underworld of corruption and gun trafficking.
- 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_69d806aee7308190b70a237ba2a6e3e1 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c9cb7ac819095cff8699993c419 |
completed | April 10, 2026, 11:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6f611b11c8190b9f89313eb2b5fab |
completed | May 3, 2026, 7:15 a.m. |
| NEDg | Description generation | batch_69f6f79703588190ba088971da54340f |
completed | May 3, 2026, 7:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6f89072a88190b3182f581b1b6762 |
completed | May 3, 2026, 7:26 a.m. |
Created at: April 9, 2026, 9:17 p.m.