Triple
T9488032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kati language |
E228811
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object | Kata-vari |
E235941
|
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: Kata-vari | Statement: [Kati language, alternativeName, Kata-vari]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kata-vari Context triple: [Kati language, alternativeName, Kata-vari]
-
A.
Kamkata-vari
chosen
Kamkata-vari is an Indo-Iranian (Nuristani) language spoken primarily in parts of Afghanistan and Pakistan, encompassing several closely related dialects including Kamviri.
-
B.
Varekai
Varekai is a Cirque du Soleil touring circus production known for its fantastical forest setting, acrobatic performances, and imaginative storytelling.
-
C.
Karekari
Karekari is an alternative name for Karekare, a coastal settlement in West Auckland, New Zealand, known for its rugged black-sand surf beach and dramatic landscapes.
-
D.
Kataki Odia
Kataki Odia is a regional dialect of the Odia language spoken in and around the city of Cuttack in the Indian state of Odisha.
-
E.
Kibushi
Kibushi is a Bantu language spoken primarily in Mayotte, where it serves as one of the island’s main regional languages.
- 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_69ca847424f081908180305555139f7a |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd80c443b88190968d2092a73e1ee4 |
completed | April 1, 2026, 8:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d12d18fd908190b562fa0a8dad7c63 |
completed | April 4, 2026, 3:24 p.m. |
Created at: March 30, 2026, 7:55 p.m.