Triple
T11902371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lionel Bernstein |
E283183
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Hilda Bernstein
Hilda Bernstein was a British-born South African anti-apartheid activist, feminist, and author who played a prominent role in the struggle against racial segregation.
|
E1021353
|
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: Hilda Bernstein | Statement: [Lionel Bernstein, spouse, Hilda Bernstein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hilda Bernstein Context triple: [Lionel Bernstein, spouse, Hilda Bernstein]
-
A.
Freda Bernstein
Freda Bernstein was the wife of British composer Lennox Berkeley and a figure associated with his personal and musical life.
-
B.
Evelyn Meltzer
Evelyn Meltzer is an individual notable enough to be recognized as a prominent bearer of the surname Meltzer.
-
C.
Helene Shapiro
Helene Shapiro is an American mathematician known for her work in linear algebra and matrix theory, and as a student of Olga Taussky-Todd.
-
D.
Evelyn Bernstein
Evelyn Bernstein was the wife of renowned American film composer Elmer Bernstein.
-
E.
Carmen Bernstein
Carmen Bernstein is a sharp-tongued, no-nonsense theater producer and comic character in the musical whodunit "Curtains."
- 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: Hilda Bernstein Triple: [Lionel Bernstein, spouse, Hilda Bernstein]
Generated description
Hilda Bernstein was a British-born South African anti-apartheid activist, feminist, and author who played a prominent role in the struggle against racial segregation.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hilda Bernstein Target entity description: Hilda Bernstein was a British-born South African anti-apartheid activist, feminist, and author who played a prominent role in the struggle against racial segregation.
-
A.
Freda Bernstein
Freda Bernstein was the wife of British composer Lennox Berkeley and a figure associated with his personal and musical life.
-
B.
Evelyn Meltzer
Evelyn Meltzer is an individual notable enough to be recognized as a prominent bearer of the surname Meltzer.
-
C.
Helene Shapiro
Helene Shapiro is an American mathematician known for her work in linear algebra and matrix theory, and as a student of Olga Taussky-Todd.
-
D.
Evelyn Bernstein
Evelyn Bernstein was the wife of renowned American film composer Elmer Bernstein.
-
E.
Carmen Bernstein
Carmen Bernstein is a sharp-tongued, no-nonsense theater producer and comic character in the musical whodunit "Curtains."
- 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_69d6ab2c07e88190ba13b0d21fd6cf33 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8dd1792648190853f15fbf217eebd |
completed | April 10, 2026, 11:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6e2548a848190a3a72415a5e4d0fd |
completed | May 3, 2026, 5:51 a.m. |
| NEDg | Description generation | batch_69f6e32bf5508190b4dc58971f8f64d0 |
completed | May 3, 2026, 5:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6e407dd988190b928b8931985a815 |
completed | May 3, 2026, 5:58 a.m. |
Created at: April 8, 2026, 9:44 p.m.