Triple
T13140204
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brassed Off |
E312191
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Greg Smith
Greg Smith is a film producer best known for his work on the British comedy-drama "Brassed Off."
|
E1032365
|
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: Greg Smith | Statement: [Brassed Off, producer, Greg Smith]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Greg Smith Context triple: [Brassed Off, producer, Greg Smith]
-
A.
Greg Smith
Greg Smith is a British Conservative Party politician who has served as the Member of Parliament for the Buckingham constituency.
-
B.
Phil Smith
Phil Smith was an American professional basketball player best known as a two-time NBA All-Star guard and key contributor to the Golden State Warriors’ 1975 championship team.
-
C.
Nick Smith
Nick Smith is the doomed husband and diner owner whose murder becomes the central plot of the 1946 film noir "The Postman Always Rings Twice."
-
D.
Mark Smith
Mark Smith is a renowned designer known for his influential work with Nike, including creating iconic basketball-related trophies and products.
-
E.
Gregory Smith
Gregory Smith is an American actor best known for his roles in film and television, including prominent performances in dramas and family series.
- 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: Greg Smith Triple: [Brassed Off, producer, Greg Smith]
Generated description
Greg Smith is a film producer best known for his work on the British comedy-drama "Brassed Off."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Greg Smith Target entity description: Greg Smith is a film producer best known for his work on the British comedy-drama "Brassed Off."
-
A.
Greg Smith
Greg Smith is a British Conservative Party politician who has served as the Member of Parliament for the Buckingham constituency.
-
B.
Phil Smith
Phil Smith was an American professional basketball player best known as a two-time NBA All-Star guard and key contributor to the Golden State Warriors’ 1975 championship team.
-
C.
Nick Smith
Nick Smith is the doomed husband and diner owner whose murder becomes the central plot of the 1946 film noir "The Postman Always Rings Twice."
-
D.
Mark Smith
Mark Smith is a renowned designer known for his influential work with Nike, including creating iconic basketball-related trophies and products.
-
E.
Gregory Smith
Gregory Smith is an American actor best known for his roles in film and television, including prominent performances in dramas and family series.
- 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_69d806aabde48190899e13e41659cae5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d981b84f1081908b9e2d54a64d4c2d |
completed | April 10, 2026, 11:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f716bf10f48190b20d0358cf5fbc9e |
completed | May 3, 2026, 9:34 a.m. |
| NEDg | Description generation | batch_69f7177e07508190b46e6a12f09e7986 |
completed | May 3, 2026, 9:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f717e72b988190927b628022bcbf12 |
completed | May 3, 2026, 9:39 a.m. |
Created at: April 9, 2026, 9:09 p.m.