Triple
T11235061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Bad Seed |
E265921
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Evelyn Varden
Evelyn Varden was an American character actress known for her memorable supporting roles in mid-20th-century films and stage productions.
|
E913089
|
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: Evelyn Varden | Statement: [The Bad Seed, starring, Evelyn Varden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Evelyn Varden Context triple: [The Bad Seed, starring, Evelyn Varden]
-
A.
Evelyn Rothwell
Evelyn Rothwell was a renowned English oboist celebrated for her solo performances and influential role in 20th-century classical music.
-
B.
Evelyn Ankers
Evelyn Ankers was a British-American actress best known as a leading lady in 1940s Universal horror films.
-
C.
Mary Tuffley
Mary Tuffley was the wife of English writer Daniel Defoe, known primarily through her marriage to the famed author of "Robinson Crusoe."
-
D.
Mary Tuffley
Mary Tuffley is an individual whose specific public background or notable achievements are not clearly documented in widely available sources.
-
E.
Beryl Vertue
Beryl Vertue was a prominent British television producer and media executive known for her influential work in comedy and for founding the production company Hartswood Films.
- 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: Evelyn Varden Triple: [The Bad Seed, starring, Evelyn Varden]
Generated description
Evelyn Varden was an American character actress known for her memorable supporting roles in mid-20th-century films and stage productions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Evelyn Varden Target entity description: Evelyn Varden was an American character actress known for her memorable supporting roles in mid-20th-century films and stage productions.
-
A.
Evelyn Rothwell
Evelyn Rothwell was a renowned English oboist celebrated for her solo performances and influential role in 20th-century classical music.
-
B.
Evelyn Ankers
Evelyn Ankers was a British-American actress best known as a leading lady in 1940s Universal horror films.
-
C.
Mary Tuffley
Mary Tuffley was the wife of English writer Daniel Defoe, known primarily through her marriage to the famed author of "Robinson Crusoe."
-
D.
Mary Tuffley
Mary Tuffley is an individual whose specific public background or notable achievements are not clearly documented in widely available sources.
-
E.
Beryl Vertue
Beryl Vertue was a prominent British television producer and media executive known for her influential work in comedy and for founding the production company Hartswood Films.
- 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_69d6aac656d48190b275efaa7d6074ee |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e903b8ec81909f9c89776d35c650 |
completed | April 9, 2026, 5:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4ad56013481909f931505824e3b42 |
completed | April 19, 2026, 10:24 a.m. |
| NEDg | Description generation | batch_69e4b12dd658819085c25d3edac2d66c |
completed | April 19, 2026, 10:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e4b3e05b488190bf2e3810ba2f250e |
completed | April 19, 2026, 10:52 a.m. |
Created at: April 8, 2026, 9:30 p.m.