Triple
T1813168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mali |
E40373
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Gao |
E144681
|
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: Gao | Statement: [Mali, containsCity, Gao]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gao Context triple: [Mali, containsCity, Gao]
-
A.
Gao
Gao is a Chinese surname historically associated with the Jewish community of Kaifeng, one of the oldest Jewish diasporas in China.
-
B.
Gao
chosen
Gao is a historic city in eastern Mali that served as a major trading center and former capital of the Songhai Empire along the Niger River.
-
C.
Xuan
Xuan is a Vietnamese surname commonly used as a family name in Vietnam.
-
D.
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.
-
E.
Guanggu
Guanggu is a major high-tech development zone in Wuhan, China, known as an innovation hub for the optics and electronics industries.
- 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_69a88643a3388190a612f2ebe1fb29e7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa65c775408190b4f5912786720e28 |
completed | March 6, 2026, 5:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adbf5b1dbc8190a57430bf129173e4 |
completed | March 8, 2026, 6:26 p.m. |
Created at: March 4, 2026, 7:32 p.m.