Triple
T5140737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guy Kibbee |
E115943
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Helen Shay
Helen Shay was the wife of American character actor Guy Kibbee, known for his roles in 1930s and 1940s Hollywood films.
|
E505569
|
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: Helen Shay | Statement: [Guy Kibbee, spouse, Helen Shay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Helen Shay Context triple: [Guy Kibbee, spouse, Helen Shay]
-
A.
Helen Rose
Helen Rose was an acclaimed American costume designer best known for her glamorous work at MGM during Hollywood’s Golden Age, creating iconic wardrobes for stars like Elizabeth Taylor and Grace Kelly.
-
B.
Helen Hughes
Helen Hughes was a daughter of Charles Evans Hughes, the prominent American statesman who served as both U.S. Secretary of State and Chief Justice of the Supreme Court.
-
C.
Helen Willis
Helen Willis is a central character on the sitcom "The Jeffersons," known as Louise Jefferson’s close friend and one half of the show’s groundbreaking interracial couple.
-
D.
Helen Flint
Helen Flint is a television and film producer known for her work as an executive producer on high-profile drama series.
-
E.
Helene Bradley
Helene Bradley is a fictional character appearing in Ernest Hemingway’s novel "To Have and Have Not."
- 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: Helen Shay Triple: [Guy Kibbee, spouse, Helen Shay]
Generated description
Helen Shay was the wife of American character actor Guy Kibbee, known for his roles in 1930s and 1940s Hollywood films.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Helen Shay Target entity description: Helen Shay was the wife of American character actor Guy Kibbee, known for his roles in 1930s and 1940s Hollywood films.
-
A.
Helen Rose
Helen Rose was an acclaimed American costume designer best known for her glamorous work at MGM during Hollywood’s Golden Age, creating iconic wardrobes for stars like Elizabeth Taylor and Grace Kelly.
-
B.
Helen Hughes
Helen Hughes was a daughter of Charles Evans Hughes, the prominent American statesman who served as both U.S. Secretary of State and Chief Justice of the Supreme Court.
-
C.
Helen Willis
Helen Willis is a central character on the sitcom "The Jeffersons," known as Louise Jefferson’s close friend and one half of the show’s groundbreaking interracial couple.
-
D.
Helen Flint
Helen Flint is a television and film producer known for her work as an executive producer on high-profile drama series.
-
E.
Helene Bradley
Helene Bradley is a fictional character appearing in Ernest Hemingway’s novel "To Have and Have Not."
- 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_69bd44459a988190a772a5c2ec6a1965 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd787e5fe88190834042a73d4d9619 |
completed | March 20, 2026, 4:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bef7f117ac8190a03379437484627b |
completed | March 21, 2026, 7:56 p.m. |
| NEDg | Description generation | batch_69bef933c4008190bea3a5a7e5de17e6 |
completed | March 21, 2026, 8:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bef9a600908190bdaff60b7a514538 |
completed | March 21, 2026, 8:03 p.m. |
Created at: March 20, 2026, 1:43 p.m.