Triple
T10314204
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roger E. Mosley |
E241971
|
entity |
| Predicate | appearedIn |
P795
|
FINISHED |
| Object |
Baretta
Baretta is a 1970s American television crime drama series centered on an unconventional undercover police detective.
|
E855830
|
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: Baretta | Statement: [Roger E. Mosley, appearedIn, Baretta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baretta Context triple: [Roger E. Mosley, appearedIn, Baretta]
-
A.
Luella Gear
Luella Gear was an American actress and comedian known for her work in early 20th-century stage and film productions.
-
B.
Agent 13
Agent 13 is the covert alias used by James Wilkinson, a character known as a skilled undercover operative in the Marvel universe.
-
C.
Bonnie Lisbon
Bonnie Lisbon is one of the troubled Lisbon sisters whose inner life and tragic fate are central to the haunting coming-of-age story in "The Virgin Suicides."
-
D.
Refugio Grey
Refugio Grey is a remote mountain lodge and trekking shelter in Chilean Patagonia that serves as a popular base for visitors exploring Grey Glacier and Torres del Paine National Park.
-
E.
Honey Ryder
Honey Ryder is a fictional Bond girl and shell diver who becomes James Bond’s ally and love interest in the 1962 film "Dr. No."
- 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: Baretta Triple: [Roger E. Mosley, appearedIn, Baretta]
Generated description
Baretta is a 1970s American television crime drama series centered on an unconventional undercover police detective.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Baretta Target entity description: Baretta is a 1970s American television crime drama series centered on an unconventional undercover police detective.
-
A.
Luella Gear
Luella Gear was an American actress and comedian known for her work in early 20th-century stage and film productions.
-
B.
Agent 13
Agent 13 is the covert alias used by James Wilkinson, a character known as a skilled undercover operative in the Marvel universe.
-
C.
Bonnie Lisbon
Bonnie Lisbon is one of the troubled Lisbon sisters whose inner life and tragic fate are central to the haunting coming-of-age story in "The Virgin Suicides."
-
D.
Refugio Grey
Refugio Grey is a remote mountain lodge and trekking shelter in Chilean Patagonia that serves as a popular base for visitors exploring Grey Glacier and Torres del Paine National Park.
-
E.
Honey Ryder
Honey Ryder is a fictional Bond girl and shell diver who becomes James Bond’s ally and love interest in the 1962 film "Dr. No."
- 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_69d381ac38808190a8ca7457c85b625b |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d35b7c688190b68613f28b5511bc |
completed | April 7, 2026, 9:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71d86c7e481908a0d5e65f66ab2c0 |
completed | April 9, 2026, 3:31 a.m. |
| NEDg | Description generation | batch_69d73186831481909555e2205d8783a7 |
completed | April 9, 2026, 4:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d732bfc76c819089287477b54a7b77 |
completed | April 9, 2026, 5:01 a.m. |
Created at: April 6, 2026, 11:48 a.m.