Triple
T8851750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bernadette Peters |
E210652
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Michael Wittenberg
Michael Wittenberg was an investment adviser best known as the late husband of Broadway star Bernadette Peters.
|
E780041
|
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: Michael Wittenberg | Statement: [Bernadette Peters, spouse, Michael Wittenberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Wittenberg Context triple: [Bernadette Peters, spouse, Michael Wittenberg]
-
A.
Michael Kozoll
Michael Kozoll is an American television writer and producer best known for co-creating the influential police drama series "Hill Street Blues."
-
B.
Michael Vavitch
Michael Vavitch was a silent-era film actor known for his role in the 1924 drama "The Red Lily."
-
C.
Mitch Kertzman
Mitch Kertzman is an American technology executive and entrepreneur best known for his leadership roles in the software and semiconductor industries, including at companies like LSI Logic and Sybase.
-
D.
Paul Biegler
Paul Biegler is a small-town Michigan lawyer and the central protagonist of the courtroom drama novel and film "Anatomy of a Murder."
-
E.
Guy Schuessler
Guy Schuessler is a British actor and theatre professional best known as the husband of acclaimed stage and screen actress Dame Harriet Walter.
- 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: Michael Wittenberg Triple: [Bernadette Peters, spouse, Michael Wittenberg]
Generated description
Michael Wittenberg was an investment adviser best known as the late husband of Broadway star Bernadette Peters.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michael Wittenberg Target entity description: Michael Wittenberg was an investment adviser best known as the late husband of Broadway star Bernadette Peters.
-
A.
Michael Kozoll
Michael Kozoll is an American television writer and producer best known for co-creating the influential police drama series "Hill Street Blues."
-
B.
Michael Vavitch
Michael Vavitch was a silent-era film actor known for his role in the 1924 drama "The Red Lily."
-
C.
Mitch Kertzman
Mitch Kertzman is an American technology executive and entrepreneur best known for his leadership roles in the software and semiconductor industries, including at companies like LSI Logic and Sybase.
-
D.
Paul Biegler
Paul Biegler is a small-town Michigan lawyer and the central protagonist of the courtroom drama novel and film "Anatomy of a Murder."
-
E.
Guy Schuessler
Guy Schuessler is a British actor and theatre professional best known as the husband of acclaimed stage and screen actress Dame Harriet Walter.
- 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_69ca838a424c8190b1ecac115c2927e7 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc60c3c5548190926e374bbe592180 |
completed | April 1, 2026, 12:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d04729c39c8190a88a28288653399b |
completed | April 3, 2026, 11:03 p.m. |
| NEDg | Description generation | batch_69d0489f19808190b793dac8c0f743bc |
completed | April 3, 2026, 11:09 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d0496ccb908190b9ebe632df1447be |
completed | April 3, 2026, 11:12 p.m. |
Created at: March 30, 2026, 6:49 p.m.