Triple
T17630655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mia |
E429966
|
entity |
| Predicate | hasVariantForm |
P457
|
FINISHED |
| Object | Miah |
—
|
NE NERFINISHED |
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: Miah | Statement: [Mia, hasVariantForm, Miah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Miah Context triple: [Mia, hasVariantForm, Miah]
-
A.
Mija
Mija is the brave young girl protagonist of the film "Okja," who risks everything to rescue her genetically engineered super-pig friend from a powerful corporation.
-
B.
Millyea
Millyea is a notable summit located within the Dungeon Hills range.
-
C.
Mishael
Mishael is one of the three Hebrew youths in the biblical additions to Daniel who, along with his companions, is miraculously preserved in the fiery furnace.
-
D.
Mia
chosen
Mia is a feminine given name used in many cultures, often as a short form of names like Maria or Amelia.
-
E.
Mia
Mia is a major fine art museum in Minneapolis, Minnesota, known for its extensive and diverse collection spanning thousands of years and cultures.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889e37f308190a6aa0a69daff86c7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46dc01b1c819099e3329cfb8cb77f |
completed | April 19, 2026, 5:53 a.m. |
Created at: April 10, 2026, 5:52 a.m.