Triple
T13109234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaitlin |
E310926
|
entity |
| Predicate | hasSpellingVariant |
P457
|
FINISHED |
| Object | Caitlyn |
E408615
|
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: Caitlyn | Statement: [Kaitlin, hasSpellingVariant, Caitlyn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caitlyn Context triple: [Kaitlin, hasSpellingVariant, Caitlyn]
-
A.
Caitlyn
chosen
Caitlyn is the given name of Caitlyn Jenner, the American television personality and former Olympic gold medal–winning decathlete.
-
B.
Katarina
Katarina is a feminine given name, commonly used in various European cultures, that is a variant of the name Catherine.
-
C.
Maria Lilina
Maria Lilina was a prominent Russian stage actress of the Moscow Art Theatre and the wife and close artistic collaborator of theatre director Konstantin Stanislavski.
-
D.
Leona
Leona is a feminine given name used in various cultures, often derived from the Latin word for "lion."
-
E.
Ashe
Ashe is a small village in Hampshire, England, known for its rural setting near the headwaters of the River Test.
- 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_69d806a872d08190a329806f8ff30df4 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9817ce07881909ec552bf861ac175 |
completed | April 10, 2026, 11:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6e27bd8fc8190a81130b7cb3a8bd8 |
completed | May 3, 2026, 5:51 a.m. |
Created at: April 9, 2026, 9:05 p.m.