Triple
T15972456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karina Smirnoff |
E387357
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Karina |
E1146859
|
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: Karina | Statement: [Karina Smirnoff, givenName, Karina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karina Context triple: [Karina Smirnoff, givenName, Karina]
-
A.
Karina
chosen
Karina is a retired Canadian soccer goalkeeper and Olympic bronze medalist who played for the Canadian women’s national team.
-
B.
Kaarina
Kaarina is a town and municipality in southwestern Finland, located near the city of Turku.
-
C.
Karin
Karin is a feminine given name used in various cultures, often considered a variant of names like Karen or Katherine.
-
D.
Karin
Karin is the main settlement and administrative center of Abemama Atoll in Kiribati.
-
E.
Katia
Katia is the Atlantic hurricane name that was introduced to replace the retired name Katrina following the devastating 2005 storm.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1572a8fd8819092ae1766324b1345 |
completed | April 16, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffdbc6f4c08190b816bf6d92114ad2 |
completed | May 10, 2026, 1:13 a.m. |
Created at: April 10, 2026, 4:54 a.m.