Triple
T4306471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen Christina (1933 film) |
E99965
|
entity |
| Predicate | portraysCharacter |
P1668
|
FINISHED |
| Object |
Magnus
Magnus is a character in the 1933 historical drama film "Queen Christina," which stars Greta Garbo as the Swedish monarch.
|
E429163
|
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: Magnus | Statement: [Queen Christina (1933 film), portraysCharacter, Magnus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Magnus Context triple: [Queen Christina (1933 film), portraysCharacter, Magnus]
-
A.
Magnus
Magnus is the honorific cognomen meaning "the Great," famously borne by the Roman general and statesman Pompey.
-
B.
Magnus Nolan
Magnus Nolan is one of the children of filmmaker Christopher Nolan and producer Emma Thomas, known primarily for his connection to this prominent filmmaking family.
-
C.
Magus
Magus is a mysterious spiritual master in Paulo Coelho’s novel "Brida," guiding the protagonist through her journey of self-discovery and magical initiation.
-
D.
Rigmor
Rigmor is a feminine given name of Scandinavian origin, particularly used in Norway and Denmark.
-
E.
Magni
Magni is a Norse god, one of Thor’s sons, renowned in mythology for his immense strength and survival of Ragnarök.
- 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: Magnus Triple: [Queen Christina (1933 film), portraysCharacter, Magnus]
Generated description
Magnus is a character in the 1933 historical drama film "Queen Christina," which stars Greta Garbo as the Swedish monarch.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Magnus Target entity description: Magnus is a character in the 1933 historical drama film "Queen Christina," which stars Greta Garbo as the Swedish monarch.
-
A.
Magnus
Magnus is the honorific cognomen meaning "the Great," famously borne by the Roman general and statesman Pompey.
-
B.
Magnus Nolan
Magnus Nolan is one of the children of filmmaker Christopher Nolan and producer Emma Thomas, known primarily for his connection to this prominent filmmaking family.
-
C.
Magus
Magus is a mysterious spiritual master in Paulo Coelho’s novel "Brida," guiding the protagonist through her journey of self-discovery and magical initiation.
-
D.
Rigmor
Rigmor is a feminine given name of Scandinavian origin, particularly used in Norway and Denmark.
-
E.
Magni
Magni is a Norse god, one of Thor’s sons, renowned in mythology for his immense strength and survival of Ragnarök.
- 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_69b345528ebc8190b5abc7e95094792d |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b350bb78cc8190a850aca47d8711cf |
completed | March 12, 2026, 11:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5c756809c8190af90c91ec7883e55 |
completed | March 14, 2026, 8:38 p.m. |
| NEDg | Description generation | batch_69b5c804f3f881908dd2d020d07c4859 |
completed | March 14, 2026, 8:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5c84e48b8819080571f995d8baf13 |
completed | March 14, 2026, 8:42 p.m. |
Created at: March 12, 2026, 11:09 p.m.