Triple
T6701125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastern Bantu |
E152879
|
entity |
| Predicate | hasMemberLanguage |
P7390
|
FINISHED |
| Object | Yao |
E136467
|
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: Yao | Statement: [Eastern Bantu, hasMemberLanguage, Yao]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yao Context triple: [Eastern Bantu, hasMemberLanguage, Yao]
-
A.
Yao
Yao is a city in Osaka Prefecture, Japan, known as an industrial and residential hub within the Kansai region.
-
B.
Yao
chosen
Yao is a Southern Bantu language spoken primarily in Malawi, Mozambique, and Tanzania by the Yao people.
-
C.
Yao
Yao are an ethnic minority people in southern China and Southeast Asia known for their distinct languages, traditional clothing, and mountain village communities.
-
D.
Yao
Yao is a calm, enigmatic wellness consultant at the remote health resort in Liane Moriarty’s novel (and its TV adaptation) "Nine Perfect Strangers."
-
E.
Keqiang
Keqiang is the given name of Li Keqiang, who served as the Premier of the People's Republic of China from 2013 to 2023.
- 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_69c68807adbc8190b8632df42b39eda0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d0e4a1848190997520ddd7808cc6 |
completed | March 27, 2026, 6:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c70081395c8190921636db5cfa096a |
completed | March 27, 2026, 10:11 p.m. |
Created at: March 27, 2026, 2:05 p.m.