Triple
T2732333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bob (TV series) |
E60342
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object |
Ruth Kobart
Ruth Kobart was an American character actress known for her work on stage, film, and television, including roles in Broadway productions and various TV series.
|
E340200
|
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: Ruth Kobart | Statement: [Bob (TV series), hasCastMember, Ruth Kobart]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ruth Kobart Context triple: [Bob (TV series), hasCastMember, Ruth Kobart]
-
A.
Ruth Weinstein
Ruth Weinstein is one of the children of disgraced American film producer Harvey Weinstein.
-
B.
Ruth Arnon
Ruth Arnon is an Israeli biochemist best known as a co-developer of the multiple sclerosis drug Copaxone and a prominent figure in immunology research.
-
C.
Margaret Shenberg
Margaret Shenberg was the first wife of influential Hollywood film producer and studio executive Louis B. Mayer.
-
D.
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.
-
E.
Sally Kornbluth
Sally Kornbluth is an American cell biologist and academic leader who became the 18th president of the Massachusetts Institute of Technology.
- 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: Ruth Kobart Triple: [Bob (TV series), hasCastMember, Ruth Kobart]
Generated description
Ruth Kobart was an American character actress known for her work on stage, film, and television, including roles in Broadway productions and various TV series.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ruth Kobart Target entity description: Ruth Kobart was an American character actress known for her work on stage, film, and television, including roles in Broadway productions and various TV series.
-
A.
Ruth Weinstein
Ruth Weinstein is one of the children of disgraced American film producer Harvey Weinstein.
-
B.
Ruth Arnon
Ruth Arnon is an Israeli biochemist best known as a co-developer of the multiple sclerosis drug Copaxone and a prominent figure in immunology research.
-
C.
Margaret Shenberg
Margaret Shenberg was the first wife of influential Hollywood film producer and studio executive Louis B. Mayer.
-
D.
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.
-
E.
Sally Kornbluth
Sally Kornbluth is an American cell biologist and academic leader who became the 18th president of the Massachusetts Institute of Technology.
- 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_69ab4b75cd908190b691ef0d1801acda |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdaf011548190beb9c3feee7b743f |
completed | March 7, 2026, 7:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b276bd909c8190a227ae7af6f41547 |
completed | March 12, 2026, 8:18 a.m. |
| NEDg | Description generation | batch_69b27a91eea881909cf62ec7a102e798 |
completed | March 12, 2026, 8:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b27b51403c8190a7244cc1d96bf9a4 |
completed | March 12, 2026, 8:37 a.m. |
Created at: March 6, 2026, 9:56 p.m.