Triple
T22879112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ronga language |
E567410
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | XiRonga |
—
|
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: XiRonga | Statement: [Ronga language, hasAlternativeName, XiRonga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: XiRonga Context triple: [Ronga language, hasAlternativeName, XiRonga]
-
A.
XiRonga
chosen
XiRonga is a Bantu language spoken primarily by the Ronga people in southern Mozambique and surrounding regions.
-
B.
Xianyou
Xianyou is a county in Fujian Province, China, historically and culturally significant as a center of the Pu-Xian (Puxian) Min language and regional traditions.
-
C.
Xierqi
Xierqi is a major technology and business hub in Beijing, known for its concentration of high-tech companies and convenient transportation links.
-
D.
Xing
Xing is a German-based professional networking platform focused on career development and business connections, particularly in German-speaking countries.
-
E.
ShiRonga
ShiRonga is an alternative name for the Ronga language, a Bantu language spoken primarily in southern Mozambique.
- 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_69e24589d8348190b96422d13a678bc1 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17f5a26f4819086ede6d85a2ab2bf |
completed | April 29, 2026, 3:47 a.m. |
Created at: April 17, 2026, 3:39 p.m.