Triple
T7494695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Santa Clause |
E177093
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Wendy Crewson
Wendy Crewson is a Canadian actress known for her work in film and television, including prominent roles in family comedies and dramatic series.
|
E714789
|
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: Wendy Crewson | Statement: [The Santa Clause, starring, Wendy Crewson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wendy Crewson Context triple: [The Santa Clause, starring, Wendy Crewson]
-
A.
Wendy Neuss
Wendy Neuss is an American television producer best known for her work on Star Trek-related projects and for her past marriage to actor Patrick Stewart.
-
B.
Jessica Congdon
Jessica Congdon is a filmmaker and editor best known for her work producing the documentary "Miss Representation," which examines the portrayal of women in the media.
-
C.
Melissa Parmenter
Melissa Parmenter is a British composer and producer known for her film scores and frequent collaborations with director Michael Winterbottom.
-
D.
Corinne Kingsbury
Corinne Kingsbury is an American television writer and producer known for creating the series "In the Dark" and "Fam."
-
E.
Michelle Mylett
Michelle Mylett is a Canadian actress best known for playing Katy on the comedy series "Letterkenny."
- 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: Wendy Crewson Triple: [The Santa Clause, starring, Wendy Crewson]
Generated description
Wendy Crewson is a Canadian actress known for her work in film and television, including prominent roles in family comedies and dramatic series.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wendy Crewson Target entity description: Wendy Crewson is a Canadian actress known for her work in film and television, including prominent roles in family comedies and dramatic series.
-
A.
Wendy Neuss
Wendy Neuss is an American television producer best known for her work on Star Trek-related projects and for her past marriage to actor Patrick Stewart.
-
B.
Jessica Congdon
Jessica Congdon is a filmmaker and editor best known for her work producing the documentary "Miss Representation," which examines the portrayal of women in the media.
-
C.
Melissa Parmenter
Melissa Parmenter is a British composer and producer known for her film scores and frequent collaborations with director Michael Winterbottom.
-
D.
Corinne Kingsbury
Corinne Kingsbury is an American television writer and producer known for creating the series "In the Dark" and "Fam."
-
E.
Michelle Mylett
Michelle Mylett is a Canadian actress best known for playing Katy on the comedy series "Letterkenny."
- 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_69c69f2583808190bd1a4936c42a5815 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f57b5b4c8190ab839e6a98ee86ed |
completed | March 27, 2026, 9:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccbd5d671481908ecbdb8ce6ef898a |
completed | April 1, 2026, 6:38 a.m. |
| NEDg | Description generation | batch_69ccc24a39f88190995f076d1a7ec3e7 |
completed | April 1, 2026, 6:59 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ccc37f0ca88190b4e077f23dbbe6f8 |
completed | April 1, 2026, 7:04 a.m. |
Created at: March 27, 2026, 3:43 p.m.