Triple
T6538666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laura (film) |
E168229
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object |
Betty Reinhardt
Betty Reinhardt was a screenwriter best known for her work on the classic 1944 film noir "Laura."
|
E774966
|
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 Reinhardt | Statement: [Laura (film), screenwriter, Betty Reinhardt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Betty Reinhardt Context triple: [Laura (film), screenwriter, Betty Reinhardt]
-
A.
Betty Lou Bredemus
Betty Lou Bredemus was an American acting coach and theater professional best known as the mother of actress Julia Roberts.
-
B.
Betty Haas
Betty Haas is known as the former wife of American politician and longtime U.S. Senator Joe Lieberman.
-
C.
Betty McGlown
Betty McGlown was an original member of the vocal group that would later become the legendary Motown act The Supremes.
-
D.
Dorothy Goetz
Dorothy Goetz was the first wife of American composer Irving Berlin, remembered largely for her brief marriage and early death, which deeply influenced his later work.
-
E.
Bernice Stegers
Bernice Stegers is a British actress known for her work in film, television, and theatre, including roles in productions such as "Four Weddings and a Funeral" and various British TV dramas.
- 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 Reinhardt Triple: [Laura (film), screenwriter, Betty Reinhardt]
Generated description
Betty Reinhardt was a screenwriter best known for her work on the classic 1944 film noir "Laura."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Betty Reinhardt Target entity description: Betty Reinhardt was a screenwriter best known for her work on the classic 1944 film noir "Laura."
-
A.
Betty Lou Bredemus
Betty Lou Bredemus was an American acting coach and theater professional best known as the mother of actress Julia Roberts.
-
B.
Betty Haas
Betty Haas is known as the former wife of American politician and longtime U.S. Senator Joe Lieberman.
-
C.
Betty McGlown
Betty McGlown was an original member of the vocal group that would later become the legendary Motown act The Supremes.
-
D.
Dorothy Goetz
Dorothy Goetz was the first wife of American composer Irving Berlin, remembered largely for her brief marriage and early death, which deeply influenced his later work.
-
E.
Bernice Stegers
Bernice Stegers is a British actress known for her work in film, television, and theatre, including roles in productions such as "Four Weddings and a Funeral" and various British TV dramas.
- 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_69c68a51564081909e93aee0dbd9cca3 |
completed | March 27, 2026, 1:46 p.m. |
| NER | Named-entity recognition | batch_69c6add4b7f881909e485325c353f51c |
completed | March 27, 2026, 4:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfeaaf9ea0819091bd0981068e5a72 |
completed | April 3, 2026, 4:28 p.m. |
| NEDg | Description generation | batch_69cfec2bde708190b73c7672625e912d |
completed | April 3, 2026, 4:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfee809b54819089d4d0d5c555e428 |
completed | April 3, 2026, 4:44 p.m. |
Created at: March 27, 2026, 1:49 p.m.