Triple
T1403474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cory |
E31637
|
entity |
| Predicate | hasSpellingVariant |
P457
|
FINISHED |
| Object | Kory |
E167006
|
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: Kory | Statement: [Cory, hasSpellingVariant, Kory]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kory Context triple: [Cory, hasSpellingVariant, Kory]
-
A.
Cory
Cory is a masculine given name commonly used in English-speaking countries, often as a short form of names like Corey or Cornelius.
-
B.
Korina
Korina is the surname of Irina Korina, a contemporary Russian artist known for her installations and sculptural works.
-
C.
Kori
chosen
Kori is a given name, often used as a variant spelling of Cory or Corey.
-
D.
Kip
Kip is a young Sikh British-Indian army sapper in Michael Ondaatje’s novel "The English Patient," whose expertise in bomb disposal and complex relationship with the other characters explore themes of war, identity, and colonialism.
-
E.
Kadan
Kadan was a Mongol prince and military commander who played a key role in the Mongol invasions of Central and Eastern Europe in the 13th century.
- 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_69a49918e1f88190ba610f9dc8114578 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c3a0330c8190b22452d29c79fcf4 |
completed | March 1, 2026, 10:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad159920d48190ace6bc4d37af75eb |
completed | March 8, 2026, 6:22 a.m. |
Created at: March 1, 2026, 7:59 p.m.