Triple
T13952156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michel |
E335552
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Michaël |
E114788
|
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: Michaël | Statement: [Michel, hasVariant, Michaël]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michaël Context triple: [Michel, hasVariant, Michaël]
-
A.
Michaël
chosen
Michaël is a given name, typically a French or Dutch variant of the name Michael, used for males in various European countries.
-
B.
Micheal
Micheal is a given name, typically a variant spelling of the more common name Michael.
-
C.
Michael’s
Michael’s is a national arts and crafts retail chain known for selling hobby supplies, home décor, and DIY project materials.
-
D.
Paris-Michael
Paris-Michael is the given first name of Paris Jackson, the daughter of Michael Jackson and an American model, actress, and musician.
-
E.
Michel
Michel is a fictional character appearing in Frederick Forsyth’s political thriller novel "The Dogs of War."
- 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_69d81c6081b88190b53e317c3370c8fe |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e146720819085d0f5eae558b7a4 |
completed | April 14, 2026, 12:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbac8c06ec8190a6dfceab55da5b30 |
completed | May 6, 2026, 9:03 p.m. |
Created at: April 9, 2026, 10:17 p.m.