Triple
T19829741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cayden |
E476422
|
entity |
| Predicate | hasSpellingVariant |
P457
|
FINISHED |
| Object | Kayden |
—
|
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: Kayden | Statement: [Cayden, hasSpellingVariant, Kayden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kayden Context triple: [Cayden, hasSpellingVariant, Kayden]
-
A.
Cayden
chosen
Cayden is a modern unisex given name, often considered a variant of Caden and popular in English-speaking countries.
-
B.
Braeden
Braeden is the given first name of NHL player Brady Tkachuk, a prominent American-born Canadian ice hockey forward.
-
C.
Kaylon
Kaylon are a highly advanced artificial machine species from the Orville universe, known for their collective intelligence and often adversarial stance toward biological life.
-
D.
Noah Keen
Noah Keen was a British character actor known for his numerous supporting roles in film and television from the 1950s through the 1990s.
-
E.
Aiden Mathis
Aiden Mathis is a skilled former assassin and key love interest in the TV series "Revenge," deeply entwined with Emily Thorne’s quest for vengeance.
- 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e656ccd3748190adeaed9a431f8979 |
completed | April 20, 2026, 4:39 p.m. |
Created at: April 10, 2026, 1:50 p.m.