Triple
T9939960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haakon Magnus |
E194052
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Magnus |
E811527
|
NE FINISHED |
How this triple was built (2 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: [Haakon Magnus, givenName, Magnus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Magnus Context triple: [Haakon Magnus, givenName, Magnus]
-
A.
Magnus
chosen
Magnus is a surname of likely Scandinavian or Latin origin, shared by various notable individuals including astronaut Sandra Magnus.
-
B.
Magnus
Magnus is the honorific cognomen meaning "the Great," famously borne by the Roman general and statesman Pompey.
-
C.
Magnus
Magnus is a character in the 1933 historical drama film "Queen Christina," which stars Greta Garbo as the Swedish monarch.
-
D.
Magnus
Magnus is the costumed Viking mascot character who represents the Minnesota Vikings NFL team at games and events.
-
E.
Magnus Troil
Magnus Troil is a central fictional figure in Walter Scott’s novel "The Pirate," depicted as a prominent Shetland landowner whose family and fortunes are entwined with the story’s romantic and political intrigues.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca82e409348190a393777356b80a2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb5e819e08190967b799fd236749e |
completed | April 2, 2026, 12:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d228fdb8e48190808702d48470395a |
completed | April 5, 2026, 9:18 a.m. |
Created at: March 30, 2026, 8:44 p.m.