Triple
T19789574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kumyks |
E475372
|
entity |
| Predicate | neighboringPeoples |
P11274
|
FINISHED |
| Object | Nogais |
—
|
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: Nogais | Statement: [Kumyks, neighboringPeoples, Nogais]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nogais Context triple: [Kumyks, neighboringPeoples, Nogais]
-
A.
Nogais
chosen
Nogais are a Turkic ethnic group traditionally known as semi-nomadic pastoralists of the North Caucasus and Caspian steppe regions.
-
B.
Noghere
Noghere is a locality within the municipality of Muggia in northeastern Italy, near the Gulf of Trieste.
-
C.
Nog
Nog is a Ferengi Starfleet officer from Star Trek: Deep Space Nine who becomes the first of his species to join Starfleet and undergoes significant personal growth throughout the series.
-
D.
Niegocin
Niegocin is a large, popular recreational lake in northeastern Poland’s Masurian Lake District, known for sailing, water sports, and scenic natural surroundings.
-
E.
Naju
Naju is a historic city in South Korea known for its pear cultivation and location in the southwestern province of South Jeolla.
- 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_69d8e51b014081908b263e167370529a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6538ae5108190b80eb7de6f445f02 |
completed | April 20, 2026, 4:25 p.m. |
Created at: April 10, 2026, 1:49 p.m.