Triple
T2221861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nolan |
E48157
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Sarah Nolan
Sarah Nolan is a fictional character best known as the recently divorced preschool teacher seeking love in the romantic comedy film "Must Love Dogs."
|
E246253
|
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: Sarah Nolan | Statement: [Nolan, hasNotableBearer, Sarah Nolan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sarah Nolan Context triple: [Nolan, hasNotableBearer, Sarah Nolan]
-
A.
Elizabeth Young
Elizabeth Young was an American actress active in the 1930s who appeared in several Hollywood films before retiring from the screen.
-
B.
Noma Bar
Noma Bar is an Israeli graphic designer and illustrator renowned for his minimalist, concept-driven illustrations that cleverly use negative space to create multiple layered meanings.
-
C.
Aislinn O'Sullivan
Aislinn O'Sullivan is an Irish woman best known as the wife of U2 guitarist The Edge.
-
D.
Meabh Flynn
Meabh Flynn is a British filmmaker and music video director best known for her creative collaborations with and marriage to musician Peter Gabriel.
-
E.
Beth Nolan
Beth Nolan is an American lawyer and legal scholar who served as White House Counsel to President Bill Clinton.
- 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: Sarah Nolan Triple: [Nolan, hasNotableBearer, Sarah Nolan]
Generated description
Sarah Nolan is a fictional character best known as the recently divorced preschool teacher seeking love in the romantic comedy film "Must Love Dogs."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sarah Nolan Target entity description: Sarah Nolan is a fictional character best known as the recently divorced preschool teacher seeking love in the romantic comedy film "Must Love Dogs."
-
A.
Elizabeth Young
Elizabeth Young was an American actress active in the 1930s who appeared in several Hollywood films before retiring from the screen.
-
B.
Noma Bar
Noma Bar is an Israeli graphic designer and illustrator renowned for his minimalist, concept-driven illustrations that cleverly use negative space to create multiple layered meanings.
-
C.
Aislinn O'Sullivan
Aislinn O'Sullivan is an Irish woman best known as the wife of U2 guitarist The Edge.
-
D.
Meabh Flynn
Meabh Flynn is a British filmmaker and music video director best known for her creative collaborations with and marriage to musician Peter Gabriel.
-
E.
Beth Nolan
Beth Nolan is an American lawyer and legal scholar who served as White House Counsel to President Bill Clinton.
- 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_69a88aa1ee708190862c8c378c41e9eb |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc03bfdd48190bfb96ec3e41c22dc |
completed | March 7, 2026, 6:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae65605fa481908ac5b9d837600626 |
completed | March 9, 2026, 6:14 a.m. |
| NEDg | Description generation | batch_69ae669aa29c81909770cd69d27c274c |
completed | March 9, 2026, 6:20 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae66fb7f1c8190b2bc306f06c423f1 |
completed | March 9, 2026, 6:21 a.m. |
Created at: March 4, 2026, 7:47 p.m.