Triple
T5741267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Something Borrowed |
E126618
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Sarah Baldwin
Sarah Baldwin is an actress known for appearing in the romantic comedy film "Something Borrowed."
|
E543067
|
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 Baldwin | Statement: [Something Borrowed, castMember, Sarah Baldwin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sarah Baldwin Context triple: [Something Borrowed, castMember, Sarah Baldwin]
-
A.
Kathryn Crosby
Kathryn Crosby is an American actress and singer best known for her film and television work in the 1950s and 1960s and for being the second wife of entertainer Bing Crosby.
-
B.
Kim Porter
Kim Porter was an American model and actress best known for her longtime relationship with Sean "Diddy" Combs and her work in fashion and entertainment.
-
C.
Caroline Pitts
Caroline Pitts was the wife of U.S. Supreme Court Justice Henry Billings Brown.
-
D.
Anne Williamson
Anne Williamson is a musician best known for her past role as a member of the American indie folk band Lord Huron.
-
E.
Melissa Franklin
Melissa Franklin is a Canadian-American experimental particle physicist known for her work at CERN and as the first woman to receive tenure in Harvard University's physics department.
- 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 Baldwin Triple: [Something Borrowed, castMember, Sarah Baldwin]
Generated description
Sarah Baldwin is an actress known for appearing in the romantic comedy film "Something Borrowed."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sarah Baldwin Target entity description: Sarah Baldwin is an actress known for appearing in the romantic comedy film "Something Borrowed."
-
A.
Kathryn Crosby
Kathryn Crosby is an American actress and singer best known for her film and television work in the 1950s and 1960s and for being the second wife of entertainer Bing Crosby.
-
B.
Kim Porter
Kim Porter was an American model and actress best known for her longtime relationship with Sean "Diddy" Combs and her work in fashion and entertainment.
-
C.
Caroline Pitts
Caroline Pitts was the wife of U.S. Supreme Court Justice Henry Billings Brown.
-
D.
Anne Williamson
Anne Williamson is a musician best known for her past role as a member of the American indie folk band Lord Huron.
-
E.
Melissa Franklin
Melissa Franklin is a Canadian-American experimental particle physicist known for her work at CERN and as the first woman to receive tenure in Harvard University's physics department.
- 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_69c0083179548190b384b0bf3c08ca4d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0258382908190af8787feb1e5fbcd |
completed | March 22, 2026, 5:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07e1bfe4481908740aa20d55ec8f6 |
completed | March 22, 2026, 11:41 p.m. |
| NEDg | Description generation | batch_69c08a2bc1b08190998a7e5eb8d6d6ac |
completed | March 23, 2026, 12:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c08a85b508819088464b97b6c9bb99 |
completed | March 23, 2026, 12:34 a.m. |
Created at: March 22, 2026, 3:48 p.m.