Triple
T12992192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Apted |
E321931
|
entity |
| Predicate | directed |
P7373
|
FINISHED |
| Object |
Agatha
Agatha is a 1979 British mystery drama film that imagines the unexplained disappearance of crime writer Agatha Christie in 1926.
|
E1014062
|
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: Agatha | Statement: [Michael Apted, directed, Agatha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Agatha Context triple: [Michael Apted, directed, Agatha]
-
A.
Agatha
Agatha is a precognitive woman in the science fiction film "Minority Report" whose visions of future crimes are central to the story's plot and moral conflict.
-
B.
Agatha
Agatha is a character from the horror film "Night Monster," likely involved in the film’s eerie and suspenseful events.
-
C.
Agatha
Agatha was an 11th-century noblewoman, likely of Eastern European or possibly Hungarian or Kievan Rus' origin, best known as the mother of Edgar the Ætheling and Saint Margaret of Scotland.
-
D.
Agatha
Agatha is a young pastry chef at Mendl’s who becomes a key ally and love interest in Wes Anderson’s film "The Grand Budapest Hotel."
-
E.
Agatha
Agatha is a feminine given name of Greek origin, historically associated with Saint Agatha and meaning "good" or "kind."
- 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: Agatha Triple: [Michael Apted, directed, Agatha]
Generated description
Agatha is a 1979 British mystery drama film that imagines the unexplained disappearance of crime writer Agatha Christie in 1926.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Agatha Target entity description: Agatha is a 1979 British mystery drama film that imagines the unexplained disappearance of crime writer Agatha Christie in 1926.
-
A.
Agatha
Agatha was an 11th-century noblewoman, likely of Eastern European or possibly Hungarian or Kievan Rus' origin, best known as the mother of Edgar the Ætheling and Saint Margaret of Scotland.
-
B.
Agatha
Agatha is a young pastry chef at Mendl’s who becomes a key ally and love interest in Wes Anderson’s film "The Grand Budapest Hotel."
-
C.
Agatha
Agatha is a precognitive woman in the science fiction film "Minority Report" whose visions of future crimes are central to the story's plot and moral conflict.
-
D.
Agatha
Agatha is a character from the horror film "Night Monster," likely involved in the film’s eerie and suspenseful events.
-
E.
Agatha
Agatha is a feminine given name of Greek origin, historically associated with Saint Agatha and meaning "good" or "kind."
- 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_69d8076479b8819090afce3591939cdf |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e7765788190a9503ef055bc30ca |
completed | April 10, 2026, 10:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6b8fb70f481908a9a4ca04d6bf93b |
completed | May 3, 2026, 2:54 a.m. |
| NEDg | Description generation | batch_69f6baa76e8c8190b84fd31657ef3385 |
completed | May 3, 2026, 3:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6bb7a0ae08190813411fa677430aa |
completed | May 3, 2026, 3:05 a.m. |
Created at: April 9, 2026, 8:44 p.m.