Triple
T12090204
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deep State |
E287921
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Lyne Renée
Lyne Renée is a Belgian actress known for her work in international film and television, including prominent roles in series such as "Deep State."
|
E962519
|
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: Lyne Renée | Statement: [Deep State, starring, Lyne Renée]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lyne Renée Context triple: [Deep State, starring, Lyne Renée]
-
A.
Laura Davenport
Laura Davenport is the daughter of English actor Nigel Davenport.
-
B.
Lisa Lynne
Lisa Lynne is an American Celtic harpist and composer known for her melodic, folk-inspired instrumental music and collaborations in the new age and world music genres.
-
C.
Rachelle Lefevre
Rachelle Lefevre is a Canadian actress best known for her roles in the Twilight film series and various American television dramas.
-
D.
Eva Gaëlle Green
Eva Gaëlle Green is a French actress and model known for her dark, enigmatic screen presence in films such as "Casino Royale," "Penny Dreadful," and "The Dreamers."
-
E.
Nicole Durant
Nicole Durant is a supporting character in the 2006 comedy film "The Pink Panther," involved in the mystery surrounding the famous diamond theft.
- 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: Lyne Renée Triple: [Deep State, starring, Lyne Renée]
Generated description
Lyne Renée is a Belgian actress known for her work in international film and television, including prominent roles in series such as "Deep State."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lyne Renée Target entity description: Lyne Renée is a Belgian actress known for her work in international film and television, including prominent roles in series such as "Deep State."
-
A.
Laura Davenport
Laura Davenport is the daughter of English actor Nigel Davenport.
-
B.
Lisa Lynne
Lisa Lynne is an American Celtic harpist and composer known for her melodic, folk-inspired instrumental music and collaborations in the new age and world music genres.
-
C.
Rachelle Lefevre
Rachelle Lefevre is a Canadian actress best known for her roles in the Twilight film series and various American television dramas.
-
D.
Eva Gaëlle Green
Eva Gaëlle Green is a French actress and model known for her dark, enigmatic screen presence in films such as "Casino Royale," "Penny Dreadful," and "The Dreamers."
-
E.
Nicole Durant
Nicole Durant is a supporting character in the 2006 comedy film "The Pink Panther," involved in the mystery surrounding the famous diamond theft.
- 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_69d6ab4964708190850585628b287b0c |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915161f848190a6355c1e372eadaa |
completed | April 10, 2026, 3:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f66b2eb48190bae469d1dd82b119 |
completed | May 2, 2026, 1:04 p.m. |
| NEDg | Description generation | batch_69f5fd79da748190b3f0dd7d7a46314d |
completed | May 2, 2026, 1:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f5feeeeb2081908191b1c2d1c2fbfd |
completed | May 2, 2026, 1:41 p.m. |
Created at: April 8, 2026, 9:48 p.m.