Triple
T10366235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Croupier |
E244257
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Christine Ruppert
Christine Ruppert is a film producer best known for her work on the British neo-noir drama "Croupier."
|
E857422
|
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: Christine Ruppert | Statement: [Croupier, producer, Christine Ruppert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christine Ruppert Context triple: [Croupier, producer, Christine Ruppert]
-
A.
Lynn Merrill
Lynn Merrill is an individual notable enough to be recognized as a bearer of the surname Merrill.
-
B.
Christine Forrest
Christine Forrest is an American actress and producer best known for her long-time collaboration and marriage with horror filmmaker George A. Romero.
-
C.
Heidi Sutter
Heidi Sutter is an individual notable enough within her field or community to be recognized as a prominent bearer of the Sutter surname.
-
D.
Christine Dunbar Sarbanes
Christine Dunbar Sarbanes was the wife of longtime U.S. Senator Paul Sarbanes and a prominent figure in Maryland civic and community life.
-
E.
Ronna
Ronna is a residential district within Södertälje Municipality in Sweden, known for its diverse population and suburban character.
- 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: Christine Ruppert Triple: [Croupier, producer, Christine Ruppert]
Generated description
Christine Ruppert is a film producer best known for her work on the British neo-noir drama "Croupier."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Christine Ruppert Target entity description: Christine Ruppert is a film producer best known for her work on the British neo-noir drama "Croupier."
-
A.
Lynn Merrill
Lynn Merrill is an individual notable enough to be recognized as a bearer of the surname Merrill.
-
B.
Christine Forrest
Christine Forrest is an American actress and producer best known for her long-time collaboration and marriage with horror filmmaker George A. Romero.
-
C.
Heidi Sutter
Heidi Sutter is an individual notable enough within her field or community to be recognized as a prominent bearer of the Sutter surname.
-
D.
Christine Dunbar Sarbanes
Christine Dunbar Sarbanes was the wife of longtime U.S. Senator Paul Sarbanes and a prominent figure in Maryland civic and community life.
-
E.
Ronna
Ronna is a residential district within Södertälje Municipality in Sweden, known for its diverse population and suburban character.
- 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_69d381b3e328819094b23b8edcd29b5a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e96f25f48190a41c8b0206b9238c |
completed | April 7, 2026, 11:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d750c8c7588190a31bac5b774155fe |
completed | April 9, 2026, 7:10 a.m. |
| NEDg | Description generation | batch_69d751ab890c8190b1549619049dab91 |
completed | April 9, 2026, 7:13 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d7619e97588190a1443f9438c6efc0 |
completed | April 9, 2026, 8:21 a.m. |
Created at: April 6, 2026, noon