Triple
T20268639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gary |
E499032
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Garry |
—
|
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: Garry | Statement: [Gary, hasVariant, Garry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Garry Context triple: [Gary, hasVariant, Garry]
-
A.
Garry
chosen
Garry is a masculine given name most famously borne by former world chess champion Garry Kasparov.
-
B.
Gary
Gary is an industrial city in northwest Indiana, historically known for its steel production and location within the American Rust Belt.
-
C.
Gary
Gary is a small town in McDowell County, West Virginia, historically known as a coal mining community.
-
D.
Gary
Gary is a masculine given name of English origin commonly used in the United States and other English-speaking countries.
-
E.
Garris
Garris is a surname most notably associated with American filmmaker and screenwriter Mick Garris, known for his work in the horror genre.
- 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_69da6275fa6c8190952924930adee150 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e675dbb7ac8190a40c527f2c02ca50 |
completed | April 20, 2026, 6:52 p.m. |
Created at: April 11, 2026, 11:42 p.m.