Triple
T2768587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katya |
E61396
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Katia |
E135587
|
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: Katia | Statement: [Katya, hasVariant, Katia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Katia Context triple: [Katya, hasVariant, Katia]
-
A.
Katia
chosen
Katia is the Atlantic hurricane name that was introduced to replace the retired name Katrina following the devastating 2005 storm.
-
B.
Katja
Katja is a diminutive or short form of the given name Katarina, commonly used in various Slavic and European languages.
-
C.
Kaarina
Kaarina is a town and municipality in southwestern Finland, located near the city of Turku.
-
D.
Katya
Katya is a diminutive and affectionate form of the given name Catherine, commonly used in Slavic and other European cultures.
-
E.
Stefania
Stefania is a feminine given name of Italian origin, commonly used in Italy and other European countries.
- 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_69ab4b7cd13481909174bca9809ed259 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdd6785d88190b99f99889463a962 |
completed | March 7, 2026, 8:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc6496dc88190b316d5b36bc5df67 |
completed | March 10, 2026, 7:20 a.m. |
Created at: March 6, 2026, 9:57 p.m.