Triple
T10653301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Denis Goldberg |
E251025
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Esme Bodenstein
Esme Bodenstein was the wife of South African anti-apartheid activist Denis Goldberg and a fellow supporter of the struggle against apartheid.
|
E889041
|
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: Esme Bodenstein | Statement: [Denis Goldberg, spouse, Esme Bodenstein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Esme Bodenstein Context triple: [Denis Goldberg, spouse, Esme Bodenstein]
-
A.
Julia Mann
Julia Mann was the mother of German novelist Thomas Mann and a key figure in the prominent Mann literary family.
-
B.
Agathe Natanson
Agathe Natanson is a French actress known for her work in film, television, and theater.
-
C.
Eleanor Zellman
Eleanor Zellman, better known by her stage name Eleanor Audley, was an American actress famed for her distinctive voice work in classic Disney films and for roles in mid-20th-century radio and television.
-
D.
Rachel Buchman
Rachel Buchman is the titular bride and central figure in the 2008 drama film "Rachel Getting Married," around whose wedding and family tensions the story revolves.
-
E.
Emma Flegenheimer
Emma Flegenheimer was the mother of notorious American mobster Dutch Schultz (born Arthur Flegenheimer).
- 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: Esme Bodenstein Triple: [Denis Goldberg, spouse, Esme Bodenstein]
Generated description
Esme Bodenstein was the wife of South African anti-apartheid activist Denis Goldberg and a fellow supporter of the struggle against apartheid.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Esme Bodenstein Target entity description: Esme Bodenstein was the wife of South African anti-apartheid activist Denis Goldberg and a fellow supporter of the struggle against apartheid.
-
A.
Julia Mann
Julia Mann was the mother of German novelist Thomas Mann and a key figure in the prominent Mann literary family.
-
B.
Agathe Natanson
Agathe Natanson is a French actress known for her work in film, television, and theater.
-
C.
Eleanor Zellman
Eleanor Zellman, better known by her stage name Eleanor Audley, was an American actress famed for her distinctive voice work in classic Disney films and for roles in mid-20th-century radio and television.
-
D.
Rachel Buchman
Rachel Buchman is the titular bride and central figure in the 2008 drama film "Rachel Getting Married," around whose wedding and family tensions the story revolves.
-
E.
Emma Flegenheimer
Emma Flegenheimer was the mother of notorious American mobster Dutch Schultz (born Arthur Flegenheimer).
- 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_69d6aa5a4c4881908f39be6efe5981e5 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6dff85674819099bf40c9f4fede15 |
completed | April 8, 2026, 11:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69deb07626988190a46d8a54eda156f5 |
completed | April 14, 2026, 9:24 p.m. |
| NEDg | Description generation | batch_69dec2534728819095b3693120772da9 |
completed | April 14, 2026, 10:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69dec79b1b548190a74312284f98551c |
completed | April 14, 2026, 11:02 p.m. |
Created at: April 8, 2026, 9:06 p.m.