Triple
T12077072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sokoloff |
E287577
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Alexandra Sokoloff
Alexandra Sokoloff is an American novelist and screenwriter best known for her dark thrillers and crime fiction, including the Huntress/FBI series.
|
E968992
|
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: Alexandra Sokoloff | Statement: [Sokoloff, hasNotableBearer, Alexandra Sokoloff]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alexandra Sokoloff Context triple: [Sokoloff, hasNotableBearer, Alexandra Sokoloff]
-
A.
Sofia Rosinsky
Sofia Rosinsky is an American actress best known for her starring role in the science fiction television series "Paper Girls."
-
B.
Alexandra Kostoff
Alexandra Kostoff was the first wife of American novelist and screenwriter Sidney Sheldon.
-
C.
Tatiana Schlossberg
Tatiana Schlossberg is an American journalist and author, known for her environmental reporting and as a member of the Kennedy family.
-
D.
Alexandra Yatsko
Alexandra Yatsko is a film producer known for her work on the documentary "Love, Antosha."
-
E.
Alexandra Papenfus
Alexandra Papenfus is a person after whom another individual named Alexandra was named, suggesting she holds personal or familial significance to the namer.
- 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: Alexandra Sokoloff Triple: [Sokoloff, hasNotableBearer, Alexandra Sokoloff]
Generated description
Alexandra Sokoloff is an American novelist and screenwriter best known for her dark thrillers and crime fiction, including the Huntress/FBI series.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Alexandra Sokoloff Target entity description: Alexandra Sokoloff is an American novelist and screenwriter best known for her dark thrillers and crime fiction, including the Huntress/FBI series.
-
A.
Sofia Rosinsky
Sofia Rosinsky is an American actress best known for her starring role in the science fiction television series "Paper Girls."
-
B.
Alexandra Kostoff
Alexandra Kostoff was the first wife of American novelist and screenwriter Sidney Sheldon.
-
C.
Tatiana Schlossberg
Tatiana Schlossberg is an American journalist and author, known for her environmental reporting and as a member of the Kennedy family.
-
D.
Alexandra Yatsko
Alexandra Yatsko is a film producer known for her work on the documentary "Love, Antosha."
-
E.
Alexandra Papenfus
Alexandra Papenfus is a person after whom another individual named Alexandra was named, suggesting she holds personal or familial significance to the namer.
- 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_69d6ab4846e081908ee7bbd66a6d3459 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9045ceeec81909427cae8972eed26 |
completed | April 10, 2026, 2:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60a6b2d788190975275d713c26a4e |
completed | May 2, 2026, 2:30 p.m. |
| NEDg | Description generation | batch_69f60bda16e48190af8abc0aa8ef41f0 |
completed | May 2, 2026, 2:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f60cd1668881908f43d895fcfba0aa |
completed | May 2, 2026, 2:40 p.m. |
Created at: April 8, 2026, 9:48 p.m.