Triple
T18459040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katelyn Ohashi |
E450982
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Katelyn |
—
|
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: Katelyn | Statement: [Katelyn Ohashi, givenName, Katelyn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Katelyn Context triple: [Katelyn Ohashi, givenName, Katelyn]
-
A.
Kailyn
Kailyn is a feminine given name, often considered a modern variant or stylistic spelling related to names like Kylie and Kaylin.
-
B.
Kayla
Kayla is a central character in the tech-comedy web series "Hacks," known for her over-the-top personality and chaotic presence in the workplace.
-
C.
Kayla
Kayla is a young child in Jesmyn Ward’s novel "Sing, Unburied, Sing," symbolizing innocence and hope amid her family’s struggles with racism, addiction, and generational trauma in rural Mississippi.
-
D.
Kaitlin
chosen
Kaitlin is a feminine given name commonly used in English-speaking countries, often considered a variant of Caitlin or Kathleen.
-
E.
Kaylee
Kaylee is a feminine given name, often considered a modern, creative spelling of names like Cailee, Kayleigh, or Kayla.
- 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_69d8d38345688190b565eac2e4cd7935 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e52a7cdb5c8190a399f0e4052f7d1f |
completed | April 19, 2026, 7:18 p.m. |
Created at: April 10, 2026, 11:33 a.m.