Triple
T5803324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Theatre, London |
E128679
|
entity |
| Predicate | architect |
P184
|
FINISHED |
| Object |
Christopher Brown
Christopher Brown is an architect known for his work on the National Theatre in London.
|
E548544
|
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: Christopher Brown | Statement: [National Theatre, London, architect, Christopher Brown]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christopher Brown Context triple: [National Theatre, London, architect, Christopher Brown]
-
A.
Joe Danelo
Joe Danelo is a former NFL placekicker best known for his tenure with the New York Giants in the late 1970s and early 1980s.
-
B.
Chris Brown
Chris Brown is an American singer, songwriter, dancer, and actor known for his R&B and pop hits as well as his dynamic performances.
-
C.
Chris Brown
Chris Brown is a film producer known for his work on the World War II drama "The Railway Man."
-
D.
Stephen Tyrone Williams
Stephen Tyrone Williams is an American actor known for his work on stage and screen, including prominent roles in theater productions and independent films.
-
E.
Kalief Browder
Kalief Browder was a Bronx teenager whose years-long pretrial detention and abuse at Rikers Island, despite never being convicted of a crime, became a powerful symbol of injustices in the U.S. criminal justice system.
- 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: Christopher Brown Triple: [National Theatre, London, architect, Christopher Brown]
Generated description
Christopher Brown is an architect known for his work on the National Theatre in London.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Christopher Brown Target entity description: Christopher Brown is an architect known for his work on the National Theatre in London.
-
A.
Joe Danelo
Joe Danelo is a former NFL placekicker best known for his tenure with the New York Giants in the late 1970s and early 1980s.
-
B.
Chris Brown
Chris Brown is an American singer, songwriter, dancer, and actor known for his R&B and pop hits as well as his dynamic performances.
-
C.
Chris Brown
Chris Brown is a film producer known for his work on the World War II drama "The Railway Man."
-
D.
Stephen Tyrone Williams
Stephen Tyrone Williams is an American actor known for his work on stage and screen, including prominent roles in theater productions and independent films.
-
E.
Kalief Browder
Kalief Browder was a Bronx teenager whose years-long pretrial detention and abuse at Rikers Island, despite never being convicted of a crime, became a powerful symbol of injustices in the U.S. criminal justice system.
- 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_69c00846a0d881909e46841f8e156b64 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02ad11cf0819094d8f9e4aaf099a2 |
completed | March 22, 2026, 5:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c09833017c81908da09127e8455cb6 |
completed | March 23, 2026, 1:32 a.m. |
| NEDg | Description generation | batch_69c09a38077081909873a9f43f578d36 |
completed | March 23, 2026, 1:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c09aad318c81909420fa544676ce72 |
completed | March 23, 2026, 1:43 a.m. |
Created at: March 22, 2026, 3:52 p.m.