Triple
T15105958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European route E40 |
E360786
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Semey |
E676787
|
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: Semey | Statement: [European route E40, connectsTo, Semey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Semey Context triple: [European route E40, connectsTo, Semey]
-
A.
Semey
chosen
Semey is a city in northeastern Kazakhstan known historically as Semipalatinsk, situated along the Irtysh River and notable for its cultural heritage and proximity to the former Soviet nuclear test site.
-
B.
Pavlodar
Pavlodar is a major industrial and cultural city in northeastern Kazakhstan, located on the Irtysh River.
-
C.
Yoshkar-Ola
Yoshkar-Ola is a city in central Russia that serves as the administrative, cultural, and economic center of the Mari El Republic.
-
D.
Karaganda
Karaganda is a large industrial city in central Kazakhstan known for its coal mining industry and Soviet-era history.
-
E.
Ust-Kamenogorsk
Ust-Kamenogorsk is an industrial city in northeastern Kazakhstan, known as a major center for metallurgy and winter sports.
- 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_69d85a0491ec8190830960be8fafb994 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00588f35481909674f161bf0f3918 |
completed | April 15, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fec87ce9808190a862ac5839272711 |
completed | May 9, 2026, 5:39 a.m. |
Created at: April 10, 2026, 3:05 a.m.