Triple
T6771578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siwu language |
E155055
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object | Siwu |
E155055
|
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: Siwu | Statement: [Siwu language, alternativeName, Siwu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Siwu Context triple: [Siwu language, alternativeName, Siwu]
-
A.
Hui
The Hui are a predominantly Muslim ethnic group in China known for their integration of Islamic faith with Han Chinese language and cultural practices.
-
B.
Shina
Shina is an Indo-Aryan language spoken primarily in the Gilgit-Baltistan region of Pakistan and surrounding Himalayan areas.
-
C.
Siwu language
chosen
The Siwu language is a Niger-Congo language spoken primarily in the Volta Region of Ghana by the Mawu people.
-
D.
Luoyi
Luoyi was an ancient Chinese city that served as a major political and cultural center of the Zhou dynasty.
-
E.
Lisu
The Lisu are an ethnic minority people of the mountainous regions of southwest China and neighboring countries, known for their distinct Tibeto-Burman language, traditional music, and vibrant festivals.
- 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_69c68812ef7c819099369f51febb725c |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2496fa08190895d8b625fb0d699 |
completed | March 27, 2026, 6:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c712c75b9c819099b0be616925a0b9 |
completed | March 27, 2026, 11:29 p.m. |
Created at: March 27, 2026, 2:13 p.m.