Triple
T20306162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pius Thicknesse |
E505613
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object |
Guy Henry
Guy Henry is an English actor known for his work in film, television, and theatre, including roles in the Harry Potter series and the BBC medical drama Holby City.
|
E1427026
|
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: Guy Henry | Statement: [Pius Thicknesse, portrayedBy, Guy Henry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Guy Henry Context triple: [Pius Thicknesse, portrayedBy, Guy Henry]
-
A.
Michael Kane
Michael Kane is a screenwriter best known for writing the 1983 American sports drama film "All the Right Moves."
-
B.
Michael Kane
Michael Kane is a creator known for developing the character Stefen Djordjevic.
-
C.
Robert Walter
Robert Walter is a British Conservative politician who served as a Member of Parliament, notably representing the North Dorset constituency for many years.
-
D.
Peter Cummings
Peter Cummings was an architect known for designing notable British entertainment venues, including the Manchester Apollo theatre.
-
E.
Bob Gunton
Bob Gunton is an American character actor best known for his portrayal of the strict prison warden Samuel Norton in the film "The Shawshank Redemption."
- 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: Guy Henry Triple: [Pius Thicknesse, portrayedBy, Guy Henry]
Generated description
Guy Henry is an English actor known for his work in film, television, and theatre, including roles in the Harry Potter series and the BBC medical drama Holby City.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Guy Henry Target entity description: Guy Henry is an English actor known for his work in film, television, and theatre, including roles in the Harry Potter series and the BBC medical drama Holby City.
-
A.
Michael Kane
Michael Kane is a screenwriter best known for writing the 1983 American sports drama film "All the Right Moves."
-
B.
Michael Kane
Michael Kane is a creator known for developing the character Stefen Djordjevic.
-
C.
Robert Walter
Robert Walter is a British Conservative politician who served as a Member of Parliament, notably representing the North Dorset constituency for many years.
-
D.
Peter Cummings
Peter Cummings was an architect known for designing notable British entertainment venues, including the Manchester Apollo theatre.
-
E.
Bob Gunton
Bob Gunton is an American character actor best known for his portrayal of the strict prison warden Samuel Norton in the film "The Shawshank Redemption."
- 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_69e0b4b8ab648190906e18538c250148 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6773f8f688190b616f972b9bbb28e |
completed | April 20, 2026, 6:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0870756d9c81909e3e2c70f222043d |
completed | May 16, 2026, 1:26 p.m. |
| NEDg | Description generation | batch_6a0871146b248190ac91cf010a984e1f |
completed | May 16, 2026, 1:28 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0871a818688190ad69bcf84e33d014 |
completed | May 16, 2026, 1:31 p.m. |
Created at: April 16, 2026, 11:18 a.m.