Triple
T10811122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angels with Dirty Faces |
E255100
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Laury Ferguson
Laury Ferguson is a fictional character from the classic 1938 crime drama film "Angels with Dirty Faces."
|
E897637
|
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: Laury Ferguson | Statement: [Angels with Dirty Faces, character, Laury Ferguson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laury Ferguson Context triple: [Angels with Dirty Faces, character, Laury Ferguson]
-
A.
Alyson Fouse
Alyson Fouse is an American television and film writer known for her work on comedy projects including the parody film "Scary Movie 2."
-
B.
Laurie Johnson
Laurie Johnson is a British composer and bandleader best known for his film and television scores, including his work on the satirical Cold War film "Dr. Strangelove."
-
C.
Teri Hudson
Teri Hudson is the wife of Stanley Hudson, a character from the American television series "The Office."
-
D.
Lauren Poultney
Lauren Poultney is a senior British police officer who serves as the Chief Constable of South Yorkshire Police.
-
E.
Audra Lindley
Audra Lindley was an American actress best known for her role as the quirky landlady Helen Roper on the television sitcom "Three's Company" and its spin-off "The Ropers."
- 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: Laury Ferguson Triple: [Angels with Dirty Faces, character, Laury Ferguson]
Generated description
Laury Ferguson is a fictional character from the classic 1938 crime drama film "Angels with Dirty Faces."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Laury Ferguson Target entity description: Laury Ferguson is a fictional character from the classic 1938 crime drama film "Angels with Dirty Faces."
-
A.
Alyson Fouse
Alyson Fouse is an American television and film writer known for her work on comedy projects including the parody film "Scary Movie 2."
-
B.
Laurie Johnson
Laurie Johnson is a British composer and bandleader best known for his film and television scores, including his work on the satirical Cold War film "Dr. Strangelove."
-
C.
Teri Hudson
Teri Hudson is the wife of Stanley Hudson, a character from the American television series "The Office."
-
D.
Lauren Poultney
Lauren Poultney is a senior British police officer who serves as the Chief Constable of South Yorkshire Police.
-
E.
Audra Lindley
Audra Lindley was an American actress best known for her role as the quirky landlady Helen Roper on the television sitcom "Three's Company" and its spin-off "The Ropers."
- 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_69d6aa61c15c8190a1839550c56e75e1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d733b7bfac8190b6ae34144376d6ad |
completed | April 9, 2026, 5:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e344249f648190b541c7fad7a834f5 |
completed | April 18, 2026, 8:43 a.m. |
| NEDg | Description generation | batch_69e3556ad7ec819095b3babc67ecdfd4 |
completed | April 18, 2026, 9:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e358f860f08190bfd10519ff3806aa |
completed | April 18, 2026, 10:12 a.m. |
Created at: April 8, 2026, 9:18 p.m.