Triple
T15556760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Komi-Permyak language |
E370889
|
entity |
| Predicate | spokenIn |
P2266
|
FINISHED |
| Object | Perm Krai |
E240048
|
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: Perm Krai | Statement: [Komi-Permyak language, spokenIn, Perm Krai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Perm Krai Context triple: [Komi-Permyak language, spokenIn, Perm Krai]
-
A.
Perm Krai
chosen
Perm Krai is a federal subject of Russia located on the western slopes of the Ural Mountains, serving as a historical and industrial region that bridges European and Asian Russia.
-
B.
Khatai
Khatai was the poetic pen name of Shah Ismail I, the founder of the Safavid dynasty and an influential Azerbaijani-Turkic poet.
-
C.
Bolikhamsai Province
Bolikhamsai Province is a central region of Laos known for its forested mountains, river valleys, and role as a key transit and hydropower area between the country’s north and south.
-
D.
Sasin
Sasin is a leading graduate business school based in Bangkok, Thailand, known for its MBA and executive education programs.
-
E.
Isara
Isara is the Latin name for the Isar River, a major waterway flowing through the Alps and the city of Munich in Germany.
- 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_69d85cc6cf40819091f4a5facee1ebe6 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04a97dbfc8190a98cbbac5e71ba88 |
completed | April 16, 2026, 2:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff456427988190bddea01f5cb159d9 |
completed | May 9, 2026, 2:32 p.m. |
Created at: April 10, 2026, 4:09 a.m.