Triple
T16772669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Limitless |
E407640
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Andrew Howard
Andrew Howard is a Welsh actor known for his intense character roles in film and television, including a supporting role in the thriller "Limitless."
|
E1232704
|
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: Andrew Howard | Statement: [Limitless, castMember, Andrew Howard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andrew Howard Context triple: [Limitless, castMember, Andrew Howard]
-
A.
Michael Howard
Michael Howard is a British Conservative politician who served as Leader of the Conservative Party and Leader of the Opposition in the early 2000s.
-
B.
Martin Hawke
Martin Hawke is a person notable enough to be recognized as a prominent bearer of the surname Hawke.
-
C.
Howard Donald
Howard Donald is an English singer, songwriter, and DJ best known as one of the members of the pop group Take That.
-
D.
Sir Michael Howard
Sir Michael Howard was a distinguished British military historian and academic renowned for his influential works on war, strategy, and European history.
-
E.
David Hutton
David Hutton was an American singer and actor best known for his controversial marriage to evangelist Aimee Semple McPherson in the early 1930s.
- 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: Andrew Howard Triple: [Limitless, castMember, Andrew Howard]
Generated description
Andrew Howard is a Welsh actor known for his intense character roles in film and television, including a supporting role in the thriller "Limitless."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Andrew Howard Target entity description: Andrew Howard is a Welsh actor known for his intense character roles in film and television, including a supporting role in the thriller "Limitless."
-
A.
Michael Howard
Michael Howard is a British Conservative politician who served as Leader of the Conservative Party and Leader of the Opposition in the early 2000s.
-
B.
Martin Hawke
Martin Hawke is a person notable enough to be recognized as a prominent bearer of the surname Hawke.
-
C.
Howard Donald
Howard Donald is an English singer, songwriter, and DJ best known as one of the members of the pop group Take That.
-
D.
Sir Michael Howard
Sir Michael Howard was a distinguished British military historian and academic renowned for his influential works on war, strategy, and European history.
-
E.
David Hutton
David Hutton was an American singer and actor best known for his controversial marriage to evangelist Aimee Semple McPherson in the early 1930s.
- 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_69d8839174188190909f190097207065 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b036ff788190bd9f166c3f127818 |
completed | April 18, 2026, 4:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a5361c3881909be0fb9b83a59993 |
completed | May 10, 2026, 3:33 p.m. |
| NEDg | Description generation | batch_6a00a727e66481908b98e10a8bbe9747 |
completed | May 10, 2026, 3:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00a7f776788190b1467c478b5c1a33 |
completed | May 10, 2026, 3:44 p.m. |
Created at: April 10, 2026, 5:21 a.m.