Triple
T6762750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ronga |
E154633
|
entity |
| Predicate | languageContactWith |
P22730
|
FINISHED |
| Object | Changana |
E129307
|
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: Changana | Statement: [Ronga, languageContactWith, Changana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Changana Context triple: [Ronga, languageContactWith, Changana]
-
A.
Changana
chosen
Changana is a Bantu language spoken primarily in southern Mozambique and neighboring regions, known for its significant influence on local varieties of African Portuguese.
-
B.
Chanda
Chanda was a historical kingdom associated with the Gond people, an indigenous community of central India.
-
C.
Mangaliso
Mangaliso is the middle name of Robert Sobukwe, the prominent South African anti-apartheid activist and founding leader of the Pan Africanist Congress.
-
D.
Yanaon
Yanaon is the former name of Yanam, a small coastal town in India that was once part of French India and retains a distinct Franco-Indian cultural heritage.
-
E.
Machang
Machang is a town and administrative district in the Malaysian state of Kelantan, known for its semi-urban character and role as a local commercial and educational hub.
- 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_69c688109c1c8190added9a221292af0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2160a2c8190837c608a3509c62c |
completed | March 27, 2026, 6:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c71a7b50388190b380f20f0213f0e5 |
completed | March 28, 2026, 12:02 a.m. |
Created at: March 27, 2026, 2:12 p.m.