Triple
T12576386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monguor (Tu) language |
E300215
|
entity |
| Predicate | hasDialect |
P4251
|
FINISHED |
| Object | Minhe Monguor |
E993659
|
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: Minhe Monguor | Statement: [Monguor (Tu) language, hasDialect, Minhe Monguor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Minhe Monguor Context triple: [Monguor (Tu) language, hasDialect, Minhe Monguor]
-
A.
Minhe Monguor
chosen
Minhe Monguor is a Mongolic language variety spoken by the Monguor (Tu) people in Minhe County, Qinghai Province, China.
-
B.
Toktogul
Toktogul is a town in central Kyrgyzstan known for its proximity to the Toktogul Reservoir and its role in regional hydropower and agriculture.
-
C.
Khorol
Khorol is a town in central Ukraine historically situated within the former Poltava Governorate of the Russian Empire.
-
D.
Tunuyán
Tunuyán is a city in Mendoza Province, Argentina, known for its wine-producing region in the Uco Valley at the foothills of the Andes.
-
E.
Zalingei
Zalingei is a major city in the Darfur region of western Sudan, serving as an important administrative and commercial center.
- 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_69d7bde87b648190bcd0266e9efde098 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954a629fc8190a1c3b6777aad4527 |
completed | April 10, 2026, 7:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6686395c081909410b429fce6ebf8 |
completed | May 2, 2026, 9:10 p.m. |
Created at: April 9, 2026, 4:47 p.m.