Triple
T21933202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | At the Movies |
E541622
|
entity |
| Predicate | hasPresenter |
P83
|
FINISHED |
| Object |
Elvis Mitchell
Elvis Mitchell is an American film critic and interviewer known for his insightful reviews and in-depth conversations with filmmakers and actors.
|
E1509756
|
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: Elvis Mitchell | Statement: [At the Movies, hasPresenter, Elvis Mitchell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elvis Mitchell Context triple: [At the Movies, hasPresenter, Elvis Mitchell]
-
A.
Elvis Perkins
Elvis Perkins is an American folk-rock singer-songwriter known for his introspective lyrics and atmospheric, genre-blending sound.
-
B.
Elvis Patterson
Elvis Patterson is a former American football cornerback best known for his NFL career with teams including the New York Giants and Kansas City Chiefs.
-
C.
Carl Mitchell
Carl Mitchell, better known by his stage name Twista, is a Chicago rapper renowned for his rapid-fire delivery and contributions to hip-hop.
-
D.
Carl Mitchell
Carl Mitchell is a writer associated with the German-language publication "Wetter."
-
E.
Don Mitchell
Don Mitchell was an American actor best known for his role as Mark Sanger, the wheelchair-bound detective’s assistant, on the television series "Ironside."
- 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: Elvis Mitchell Triple: [At the Movies, hasPresenter, Elvis Mitchell]
Generated description
Elvis Mitchell is an American film critic and interviewer known for his insightful reviews and in-depth conversations with filmmakers and actors.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Elvis Mitchell Target entity description: Elvis Mitchell is an American film critic and interviewer known for his insightful reviews and in-depth conversations with filmmakers and actors.
-
A.
Elvis Perkins
Elvis Perkins is an American folk-rock singer-songwriter known for his introspective lyrics and atmospheric, genre-blending sound.
-
B.
Elvis Patterson
Elvis Patterson is a former American football cornerback best known for his NFL career with teams including the New York Giants and Kansas City Chiefs.
-
C.
Carl Mitchell
Carl Mitchell, better known by his stage name Twista, is a Chicago rapper renowned for his rapid-fire delivery and contributions to hip-hop.
-
D.
Carl Mitchell
Carl Mitchell is a writer associated with the German-language publication "Wetter."
-
E.
Don Mitchell
Don Mitchell was an American actor best known for his role as Mark Sanger, the wheelchair-bound detective’s assistant, on the television series "Ironside."
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f12400a1248190b3f8f27f2aa4a858 |
completed | April 28, 2026, 9:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a60e636d0819082c3d81b051c9165 |
completed | May 18, 2026, 12:44 a.m. |
| NEDg | Description generation | batch_6a0a61b197fc8190905c86e03c1cf5b9 |
completed | May 18, 2026, 12:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a6240a5008190a745a20a51d3f239 |
completed | May 18, 2026, 12:50 a.m. |
Created at: April 16, 2026, 7:47 p.m.