Triple
T20557336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abaza |
E504752
|
entity |
| Predicate | hasDialect |
P4251
|
FINISHED |
| Object | Ashkharua Abaza |
—
|
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: Ashkharua Abaza | Statement: [Abaza, hasDialect, Ashkharua Abaza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ashkharua Abaza Context triple: [Abaza, hasDialect, Ashkharua Abaza]
-
A.
Abaza
chosen
Abaza is a Northwest Caucasian language spoken primarily in the Russian Republic of Karachay-Cherkessia, known for its complex consonant system and rich verbal morphology.
-
B.
Asbarez
Asbarez is a long-running Armenian-American newspaper that serves as a key news source and voice for the Armenian diaspora, particularly in the United States.
-
C.
Ayrarat
Ayrarat was the central and most important province of ancient Armenia, encompassing the Ararat plain and serving as a key political and cultural heartland.
-
D.
Akbaa
Akbaa is the primary demonic god and main antagonist in the fantasy role-playing game Arx Fatalis.
-
E.
Akhsar
Akhsar is a heroic figure from the Nart sagas, the traditional epic folklore of the peoples of the Caucasus.
- 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_69e0b4b6587c8190aee63dc7cff244ea |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a5de9c008190b8620628fb285e90 |
completed | April 20, 2026, 10:17 p.m. |
Created at: April 16, 2026, 11:38 a.m.