Triple
T964988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sterling Hayden |
E20817
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Betty de Noon
Betty de Noon was the wife of American actor and author Sterling Hayden, known primarily for her marriage to the Hollywood star.
|
E114632
|
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: Betty de Noon | Statement: [Sterling Hayden, spouse, Betty de Noon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Betty de Noon Context triple: [Sterling Hayden, spouse, Betty de Noon]
-
A.
Betty Garde
Betty Garde was an American stage, film, and radio actress known for her versatile character roles in mid-20th-century theater and entertainment.
-
B.
Bernice
Bernice is a feminine given name most notably borne by Bernice King, the daughter of civil rights leaders Martin Luther King Jr. and Coretta Scott King.
-
C.
Bette
Bette is the given name of American singer, actress, and comedian Bette Midler.
-
D.
Betty Blake
Betty Blake was the wife of American humorist and entertainer Will Rogers, known for supporting his career and managing family life while he rose to national fame.
-
E.
Rachel Marron
Rachel Marron is a famous pop singer and actress who becomes the client and love interest of a former Secret Service agent in the romantic thriller film "The Bodyguard."
- 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: Betty de Noon Triple: [Sterling Hayden, spouse, Betty de Noon]
Generated description
Betty de Noon was the wife of American actor and author Sterling Hayden, known primarily for her marriage to the Hollywood star.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Betty de Noon Target entity description: Betty de Noon was the wife of American actor and author Sterling Hayden, known primarily for her marriage to the Hollywood star.
-
A.
Betty Garde
Betty Garde was an American stage, film, and radio actress known for her versatile character roles in mid-20th-century theater and entertainment.
-
B.
Bernice
Bernice is a feminine given name most notably borne by Bernice King, the daughter of civil rights leaders Martin Luther King Jr. and Coretta Scott King.
-
C.
Bette
Bette is the given name of American singer, actress, and comedian Bette Midler.
-
D.
Betty Blake
Betty Blake was the wife of American humorist and entertainer Will Rogers, known for supporting his career and managing family life while he rose to national fame.
-
E.
Rachel Marron
Rachel Marron is a famous pop singer and actress who becomes the client and love interest of a former Secret Service agent in the romantic thriller film "The Bodyguard."
- 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_69a493b33d2c81909c52c369d3ca8436 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b431d61481908b53490e99670363 |
completed | March 1, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac17034cf48190bca513891cfcc444 |
completed | March 7, 2026, 12:16 p.m. |
| NEDg | Description generation | batch_69ac179226dc8190b47d312c78745ada |
completed | March 7, 2026, 12:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac1844acec81909859605d2421a588 |
completed | March 7, 2026, 12:21 p.m. |
Created at: March 1, 2026, 7:40 p.m.