Triple
T14401670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern Mansi |
E357086
|
entity |
| Predicate | hasDialectGroup |
P1254
|
FINISHED |
| Object | Sosva Mansi |
E796445
|
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: Sosva Mansi | Statement: [Northern Mansi, hasDialectGroup, Sosva Mansi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sosva Mansi Context triple: [Northern Mansi, hasDialectGroup, Sosva Mansi]
-
A.
Mansi
Mansi is the central female protagonist in the 1999 Indian musical romance film "Taal," portrayed by Aishwarya Rai.
-
B.
Mansi
chosen
The Mansi are an Indigenous Uralic-speaking people of northwestern Siberia, traditionally living along the Ob River basin and known for reindeer herding, hunting, and a rich shamanistic culture.
-
C.
Serafima
Serafima is a feminine given name of Slavic origin, commonly used in Russian-speaking countries.
-
D.
Vasishka
Vasishka was a Kushan emperor who ruled parts of northern India and Central Asia in the early 3rd century CE, known primarily from his inscriptions and coinage.
-
E.
Govardeyskaya
Govardeyskaya is a Moscow Metro station on the Kalininsko–Solntsevskaya line.
- 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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de908500048190bb6a20fe318d5c62 |
completed | April 14, 2026, 7:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd5bc424f88190ab3a1c1aec61cb40 |
completed | May 8, 2026, 3:43 a.m. |
Created at: April 10, 2026, 1:17 a.m.