Triple
T14173116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knight Riders |
E351260
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object |
Amy Ingersoll
Amy Ingersoll is an actress known for her role in the film "Knight Riders."
|
E1087056
|
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: Amy Ingersoll | Statement: [Knight Riders, hasCastMember, Amy Ingersoll]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amy Ingersoll Context triple: [Knight Riders, hasCastMember, Amy Ingersoll]
-
A.
Amy Eshleman
Amy Eshleman is an American former public librarian and education advocate best known as the wife of former Chicago mayor Lori Lightfoot.
-
B.
Jane Loring
Jane Loring was a film editor known for her work in early 20th-century American cinema.
-
C.
Sarah Snodgrass
Sarah Snodgrass is a person notable enough to be recognized as a bearer of the surname Snodgrass, though specific widely known public details about her are not clearly established.
-
D.
Mary Beth Peil
Mary Beth Peil is an American actress and singer known for her work on Broadway, in film and television, and for originating prominent roles in major stage productions.
-
E.
Elizabeth Snodgrass
Elizabeth Snodgrass is a person notable enough to be specifically cited as a bearer of the Snodgrass surname.
- 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: Amy Ingersoll Triple: [Knight Riders, hasCastMember, Amy Ingersoll]
Generated description
Amy Ingersoll is an actress known for her role in the film "Knight Riders."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Amy Ingersoll Target entity description: Amy Ingersoll is an actress known for her role in the film "Knight Riders."
-
A.
Amy Eshleman
Amy Eshleman is an American former public librarian and education advocate best known as the wife of former Chicago mayor Lori Lightfoot.
-
B.
Jane Loring
Jane Loring was a film editor known for her work in early 20th-century American cinema.
-
C.
Sarah Snodgrass
Sarah Snodgrass is a person notable enough to be recognized as a bearer of the surname Snodgrass, though specific widely known public details about her are not clearly established.
-
D.
Mary Beth Peil
Mary Beth Peil is an American actress and singer known for her work on Broadway, in film and television, and for originating prominent roles in major stage productions.
-
E.
Elizabeth Snodgrass
Elizabeth Snodgrass is a person notable enough to be specifically cited as a bearer of the Snodgrass surname.
- 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_69d8278834a08190b0f1784e58d7b99c |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61b5dcbc8190b0cfcce5e6c6d582 |
completed | April 14, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd2804956c81909409fba998a87866 |
completed | May 8, 2026, 12:02 a.m. |
| NEDg | Description generation | batch_69fd2a8d7b0c81908c80de21f7922f0a |
completed | May 8, 2026, 12:13 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd2b0c9b188190a7f096429aa92419 |
completed | May 8, 2026, 12:15 a.m. |
Created at: April 10, 2026, 1:01 a.m.