Triple
T19914427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hung |
E478626
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Lenore Bernard
Lenore Bernard is a character from the television series "Hung," which follows a struggling high school teacher who becomes a male escort.
|
E1401146
|
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: Lenore Bernard | Statement: [Hung, character, Lenore Bernard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lenore Bernard Context triple: [Hung, character, Lenore Bernard]
-
A.
Lenore Ulric
Lenore Ulric was an American stage and film actress known for her intense dramatic roles in early 20th-century theater and Hollywood cinema.
-
B.
Lorraine Bergman
Lorraine Bergman was the wife of American physicist and Nobel laureate Carl David Anderson.
-
C.
Lenore Zion
Lenore Zion is an American television writer, producer, and former stand-up comedian known for her work on series such as Ray Donovan and Channel Zero.
-
D.
Joyce Giraud
Joyce Giraud is a Puerto Rican actress, model, and television personality best known for her work in beauty pageants and reality TV, including "The Real Housewives of Beverly Hills."
-
E.
Frances Berda
Frances Berda was a composer best known for writing Nigeria’s former national anthem, “Nigeria, We Hail Thee.”
- 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: Lenore Bernard Triple: [Hung, character, Lenore Bernard]
Generated description
Lenore Bernard is a character from the television series "Hung," which follows a struggling high school teacher who becomes a male escort.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lenore Bernard Target entity description: Lenore Bernard is a character from the television series "Hung," which follows a struggling high school teacher who becomes a male escort.
-
A.
Lenore Ulric
Lenore Ulric was an American stage and film actress known for her intense dramatic roles in early 20th-century theater and Hollywood cinema.
-
B.
Lorraine Bergman
Lorraine Bergman was the wife of American physicist and Nobel laureate Carl David Anderson.
-
C.
Lenore Zion
Lenore Zion is an American television writer, producer, and former stand-up comedian known for her work on series such as Ray Donovan and Channel Zero.
-
D.
Joyce Giraud
Joyce Giraud is a Puerto Rican actress, model, and television personality best known for her work in beauty pageants and reality TV, including "The Real Housewives of Beverly Hills."
-
E.
Frances Berda
Frances Berda was a composer best known for writing Nigeria’s former national anthem, “Nigeria, We Hail Thee.”
- 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_69d8e520682081909892916424699bd5 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e659928030819085a4aafc6a0ef5c8 |
completed | April 20, 2026, 4:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07ea4fc6bc81909573e05b842ec0ab |
completed | May 16, 2026, 3:53 a.m. |
| NEDg | Description generation | batch_6a07eef4995c81909b45b0e84de19c34 |
completed | May 16, 2026, 4:13 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07ef716f68819093a9a6356080e39e |
completed | May 16, 2026, 4:15 a.m. |
Created at: April 10, 2026, 1:53 p.m.