Triple
T17223350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maxime |
E418045
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Maxim |
E338749
|
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: Maxim | Statement: [Maxime, hasVariant, Maxim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maxim Context triple: [Maxime, hasVariant, Maxim]
-
A.
Maxim
chosen
Maxim is a masculine given name of Latin origin, commonly used in Slavic and other European countries.
-
B.
Maxim Roy
Maxim Roy is a Canadian actress known for her work in film and television, including prominent roles in series such as Shadowhunters and 19-2.
-
C.
Mark Francois
Mark Francois is a British Conservative politician and Member of Parliament known for his roles in defence-related ministerial posts and his prominent support for Brexit.
-
D.
Maxwell Sheffield
Maxwell Sheffield is a wealthy, widowed Broadway producer and father of three who becomes the employer and eventual love interest of Fran Fine in the sitcom "The Nanny."
-
E.
Alexandre Rockwell
Alexandre Rockwell is an American independent film director and screenwriter known for his offbeat, character-driven movies such as "In the Soup" and his segment in the anthology film "Four Rooms."
- 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_69d886d779488190b131369541c04e7d |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42ddf2c3c8190b6adceaaefd4ccbf |
completed | April 19, 2026, 1:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0167596ab481909df59ce68c7f640e |
completed | May 11, 2026, 5:21 a.m. |
Created at: April 10, 2026, 5:38 a.m.