Triple
T6047624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Levin |
E134705
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Harry Levin
Harry Levin was an influential American literary critic and scholar known for his work on modernist literature and comparative literary studies.
|
E575952
|
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: Harry Levin | Statement: [Levin, hasNotableBearer, Harry Levin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harry Levin Context triple: [Levin, hasNotableBearer, Harry Levin]
-
A.
Efrem Zimbalist
Efrem Zimbalist was a renowned Russian-American violinist, composer, and influential pedagogue of the 20th century.
-
B.
Joseph Markovitch
Joseph Markovitch was the father of French photographer and painter Dora Maar, a key figure in the Surrealist movement and companion of Pablo Picasso.
-
C.
Sam Zimbalist
Sam Zimbalist was an American film producer best known for overseeing the epic 1959 MGM classic "Ben-Hur" and other major Hollywood productions of the mid-20th century.
-
D.
Robert Levine
Robert Levine is an American cardiologist best known as the husband of actress Mary Tyler Moore.
-
E.
George Nader
George Nader was an American film and television actor best known for his roles in 1950s Hollywood productions and later European genre 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: Harry Levin Triple: [Levin, hasNotableBearer, Harry Levin]
Generated description
Harry Levin was an influential American literary critic and scholar known for his work on modernist literature and comparative literary studies.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Harry Levin Target entity description: Harry Levin was an influential American literary critic and scholar known for his work on modernist literature and comparative literary studies.
-
A.
Efrem Zimbalist
Efrem Zimbalist was a renowned Russian-American violinist, composer, and influential pedagogue of the 20th century.
-
B.
Joseph Markovitch
Joseph Markovitch was the father of French photographer and painter Dora Maar, a key figure in the Surrealist movement and companion of Pablo Picasso.
-
C.
Sam Zimbalist
Sam Zimbalist was an American film producer best known for overseeing the epic 1959 MGM classic "Ben-Hur" and other major Hollywood productions of the mid-20th century.
-
D.
Robert Levine
Robert Levine is an American cardiologist best known as the husband of actress Mary Tyler Moore.
-
E.
George Nader
George Nader was an American film and television actor best known for his roles in 1950s Hollywood productions and later European genre 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_69c00876a69881908088a2626d3b2666 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056e70fd48190b4554e9a516a1c88 |
completed | March 22, 2026, 8:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c16ea1595c8190926a5ed8d230ab4a |
completed | March 23, 2026, 4:47 p.m. |
| NEDg | Description generation | batch_69c1c533f43881908d57b75237f3c827 |
completed | March 23, 2026, 10:56 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c1c59ef9b0819091b05cd30c07d918 |
completed | March 23, 2026, 10:58 p.m. |
Created at: March 22, 2026, 4:09 p.m.