Triple
T18731563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Afterschool |
E458045
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Alexandra Neil
Alexandra Neil is an American actress best known for her work on television soap operas and series in the 1980s and 1990s.
|
E1341412
|
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 Neil | Statement: [Afterschool, castMember, Alexandra Neil]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alexandra Neil Context triple: [Afterschool, castMember, Alexandra Neil]
-
A.
Alexandra Byrne
Alexandra Byrne is an acclaimed British costume designer known for her intricate period costumes and award-winning work in both film and theatre.
-
B.
Alexandra Marie Llewellyn
Alexandra Marie Llewellyn is best known as the second wife of American thriller novelist Tom Clancy.
-
C.
Alexandra Boycun
Alexandra Boycun is known as the spouse of the influential Hungarian-British film producer and director Alexander Korda.
-
D.
Alexandra Smith
Alexandra Smith is a television producer best known for her executive production work on the true-crime series "Dirty John."
-
E.
Alexandra Holden
Alexandra Holden is an American actress known for her roles in films like "Drop Dead Gorgeous" and appearances on television series such as "Friends" and "Ally McBeal."
- 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 Neil Triple: [Afterschool, castMember, Alexandra Neil]
Generated description
Alexandra Neil is an American actress best known for her work on television soap operas and series in the 1980s and 1990s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Alexandra Neil Target entity description: Alexandra Neil is an American actress best known for her work on television soap operas and series in the 1980s and 1990s.
-
A.
Alexandra Byrne
Alexandra Byrne is an acclaimed British costume designer known for her intricate period costumes and award-winning work in both film and theatre.
-
B.
Alexandra Marie Llewellyn
Alexandra Marie Llewellyn is best known as the second wife of American thriller novelist Tom Clancy.
-
C.
Alexandra Boycun
Alexandra Boycun is known as the spouse of the influential Hungarian-British film producer and director Alexander Korda.
-
D.
Alexandra Smith
Alexandra Smith is a television producer best known for her executive production work on the true-crime series "Dirty John."
-
E.
Alexandra Holden
Alexandra Holden is an American actress known for her roles in films like "Drop Dead Gorgeous" and appearances on television series such as "Friends" and "Ally McBeal."
- 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_69d8d393ba9c8190a8b03b04ddbb0a09 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e56d7854748190b66c4aaadfd67f29 |
completed | April 20, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a053d2f42d8819093fd6de6639afd06 |
completed | May 14, 2026, 3:10 a.m. |
| NEDg | Description generation | batch_6a053e61f6148190915f8e63d0aa6ac0 |
completed | May 14, 2026, 3:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a053ea94058819090144743376cf68f |
completed | May 14, 2026, 3:16 a.m. |
Created at: April 10, 2026, 11:51 a.m.