Triple
T2918350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greta Garbo |
E78659
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Mata Hari
Mata Hari is a 1931 American pre-Code drama film starring Greta Garbo as an exotic dancer and spy, loosely inspired by the real-life World War I figure of the same name.
|
E309908
|
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: Mata Hari | Statement: [Greta Garbo, notableWork, Mata Hari]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mata Hari Context triple: [Greta Garbo, notableWork, Mata Hari]
-
A.
Bernhardt
Bernhardt is a German-origin surname and given name, most famously associated with the legendary French stage actress Sarah Bernhardt.
-
B.
Yvonne Orlac
Yvonne Orlac is a central character in the 1935 horror film "Mad Love," serving as the wife of a famed pianist whose tragic circumstances draw her into a macabre tale of obsession and surgical horror.
-
C.
Rose Stradner
Rose Stradner was an Austrian-American actress known for her work in Hollywood films of the 1930s and 1940s.
-
D.
Brigitte
Brigitte is a French former teacher best known as the wife of Emmanuel Macron, the President of France.
-
E.
Malena
Malena is a feminine given name, commonly used in various cultures and often considered a diminutive or variant of names like Magdalena.
- 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: Mata Hari Triple: [Greta Garbo, notableWork, Mata Hari]
Generated description
Mata Hari is a 1931 American pre-Code drama film starring Greta Garbo as an exotic dancer and spy, loosely inspired by the real-life World War I figure of the same name.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mata Hari Target entity description: Mata Hari is a 1931 American pre-Code drama film starring Greta Garbo as an exotic dancer and spy, loosely inspired by the real-life World War I figure of the same name.
-
A.
Bernhardt
Bernhardt is a German-origin surname and given name, most famously associated with the legendary French stage actress Sarah Bernhardt.
-
B.
Yvonne Orlac
Yvonne Orlac is a central character in the 1935 horror film "Mad Love," serving as the wife of a famed pianist whose tragic circumstances draw her into a macabre tale of obsession and surgical horror.
-
C.
Rose Stradner
Rose Stradner was an Austrian-American actress known for her work in Hollywood films of the 1930s and 1940s.
-
D.
Brigitte
Brigitte is a French former teacher best known as the wife of Emmanuel Macron, the President of France.
-
E.
Malena
Malena is a feminine given name, commonly used in various cultures and often considered a diminutive or variant of names like Magdalena.
- 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_69ad8b0c2ad081909ff87050ae542bb9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad96a41b4c81909d8ace8ab270ed3c |
completed | March 8, 2026, 3:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b0562c5b5081908026b3f590b03aca |
completed | March 10, 2026, 5:34 p.m. |
| NEDg | Description generation | batch_69b0613dfb048190b08b01837088b9dd |
completed | March 10, 2026, 6:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b06514562881909d3b08af898406f7 |
completed | March 10, 2026, 6:38 p.m. |
Created at: March 8, 2026, 2:54 p.m.