Triple
T15199674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Best Seller |
E363232
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Mary Carver
Mary Carver was an American actress known for her work in film, television, and theater, including roles in productions such as "Best Seller" and the TV series "Simon & Simon."
|
E1144150
|
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: Mary Carver | Statement: [Best Seller, starring, Mary Carver]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mary Carver Context triple: [Best Seller, starring, Mary Carver]
-
A.
Lavinia Steward
Lavinia Steward was a benefactor whose support and legacy were honored through the naming of the Steward Observatory.
-
B.
Mary Carr
Mary Carr was an American character actress of the silent and early sound film era, often cast as kindly maternal figures.
-
C.
Elizabeth Parker
Elizabeth Parker was the daughter of Eliza Parker Todd and a member of the extended family connected to Mary Todd Lincoln.
-
D.
Elizabeth Parker
Elizabeth Parker is a British composer and sound designer best known for her electronic music and soundscapes created at the BBC Radiophonic Workshop.
-
E.
Elizabeth Carver
Elizabeth Carver is a person whose specific public background or notable achievements are not clearly identifiable from the given information.
- 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: Mary Carver Triple: [Best Seller, starring, Mary Carver]
Generated description
Mary Carver was an American actress known for her work in film, television, and theater, including roles in productions such as "Best Seller" and the TV series "Simon & Simon."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mary Carver Target entity description: Mary Carver was an American actress known for her work in film, television, and theater, including roles in productions such as "Best Seller" and the TV series "Simon & Simon."
-
A.
Lavinia Steward
Lavinia Steward was a benefactor whose support and legacy were honored through the naming of the Steward Observatory.
-
B.
Mary Carr
Mary Carr was an American character actress of the silent and early sound film era, often cast as kindly maternal figures.
-
C.
Elizabeth Parker
Elizabeth Parker was the daughter of Eliza Parker Todd and a member of the extended family connected to Mary Todd Lincoln.
-
D.
Elizabeth Parker
Elizabeth Parker is a British composer and sound designer best known for her electronic music and soundscapes created at the BBC Radiophonic Workshop.
-
E.
Elizabeth Carver
Elizabeth Carver was the wife of British Field Marshal Bernard Montgomery, 1st Viscount Montgomery of Alamein.
- 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e006b476208190a5119710c518bb1f |
completed | April 15, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fed3363f688190a5c728846bea743a |
completed | May 9, 2026, 6:24 a.m. |
| NEDg | Description generation | batch_69fed76d6a888190b44efa490df4b6d0 |
completed | May 9, 2026, 6:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69feda443c64819087cb16ce742e7cc5 |
completed | May 9, 2026, 6:55 a.m. |
Created at: April 10, 2026, 3:10 a.m.