Triple
T10396606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tin Star |
E245036
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Jenessa Grant
Jenessa Grant is a Canadian actress known for her roles in television series such as Tin Star, Orphan Black, and Reign.
|
E916592
|
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: Jenessa Grant | Statement: [Tin Star, starring, Jenessa Grant]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jenessa Grant Context triple: [Tin Star, starring, Jenessa Grant]
-
A.
Rachel Grant
Rachel Grant is a British-Filipino actress and TV presenter best known for her role as Peaceful Fountains of Desire in the James Bond film "Die Another Day."
-
B.
Jennifer Grant
Jennifer Grant is an American actress and the daughter of classic Hollywood film star Cary Grant.
-
C.
Nessa Jenkins
Nessa Jenkins is a deadpan, no-nonsense Welsh character from the British sitcom "Gavin & Stacey," known for her eccentric stories and iconic catchphrases.
-
D.
Jacelyn Reeves
Jacelyn Reeves is an American former flight attendant best known as the mother of actor Scott Eastwood and for her past relationship with Clint Eastwood.
-
E.
Amanda Lohrey
Amanda Lohrey is an acclaimed Australian novelist and essayist known for her psychologically rich fiction and contributions to contemporary Australian literature.
- 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: Jenessa Grant Triple: [Tin Star, starring, Jenessa Grant]
Generated description
Jenessa Grant is a Canadian actress known for her roles in television series such as Tin Star, Orphan Black, and Reign.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jenessa Grant Target entity description: Jenessa Grant is a Canadian actress known for her roles in television series such as Tin Star, Orphan Black, and Reign.
-
A.
Rachel Grant
Rachel Grant is a British-Filipino actress and TV presenter best known for her role as Peaceful Fountains of Desire in the James Bond film "Die Another Day."
-
B.
Jennifer Grant
Jennifer Grant is an American actress and the daughter of classic Hollywood film star Cary Grant.
-
C.
Nessa Jenkins
Nessa Jenkins is a deadpan, no-nonsense Welsh character from the British sitcom "Gavin & Stacey," known for her eccentric stories and iconic catchphrases.
-
D.
Jacelyn Reeves
Jacelyn Reeves is an American former flight attendant best known as the mother of actor Scott Eastwood and for her past relationship with Clint Eastwood.
-
E.
Amanda Lohrey
Amanda Lohrey is an acclaimed Australian novelist and essayist known for her psychologically rich fiction and contributions to contemporary Australian literature.
- 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_69d381b5116081908d85227bab6d3c0c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9cf79348190975d6c1791e3b621 |
completed | April 7, 2026, 11:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e50983ce848190ab375145019ff69b |
completed | April 19, 2026, 4:57 p.m. |
| NEDg | Description generation | batch_69e510f7bec08190989118b6e4a7fa49 |
completed | April 19, 2026, 5:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e5168c8da0819093bf61d8ea5f9e35 |
completed | April 19, 2026, 5:53 p.m. |
Created at: April 6, 2026, 12:06 p.m.