Triple
T10201978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red 2 |
E238903
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Katja |
E263536
|
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: Katja | Statement: [Red 2, hasCharacter, Katja]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Katja Context triple: [Red 2, hasCharacter, Katja]
-
A.
Katja
chosen
Katja is a diminutive or short form of the given name Katarina, commonly used in various Slavic and European languages.
-
B.
Katia
Katia is the Atlantic hurricane name that was introduced to replace the retired name Katrina following the devastating 2005 storm.
-
C.
Katrin
Katrin is a feminine given name, commonly used in various European countries, that is a variant of the name Catherine.
-
D.
Kaja
Kaja is a diminutive or nickname commonly used for the given name Katarina.
-
E.
Kerstin
Kerstin is a feminine given name of Scandinavian origin, particularly common in Sweden and other Nordic 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_69ca84e1ea088190b38162e43d4cfa8f |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdee40cb7481908a1bf4d5636eb8ef |
completed | April 2, 2026, 4:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d317fcdf18819092d0f3f216edffdc |
completed | April 6, 2026, 2:18 a.m. |
Created at: March 30, 2026, 9:14 p.m.