Triple
T16872323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orenburg Oblast |
E421200
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Orenburg |
—
|
NE NERFINISHED |
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: Orenburg | Statement: [Orenburg Oblast, namedAfter, Orenburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orenburg Context triple: [Orenburg Oblast, namedAfter, Orenburg]
-
A.
Orenburg
chosen
Orenburg is a major city in southwestern Russia near the Ural River, historically significant as a frontier fortress and administrative center linking European Russia with Central Asia.
-
B.
Cheboksary
Cheboksary is a major city on the Volga River in western Russia and the capital of the Chuvash Republic.
-
C.
Kamyshin
Kamyshin is a significant industrial and river port city on the Volga River in southwestern Russia.
-
D.
Ulyanovka
Ulyanovka is an urban-type settlement in Leningrad Oblast, Russia, situated within the administrative boundaries of Tosnensky District.
-
E.
Omsk
Omsk is one of the largest cities in southwestern Siberia, Russia, serving as a major industrial, cultural, and transportation hub on the Irtysh River.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889d470fc8190b4aec199636c0c56 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3b7f31b448190a21e3e4d1a0d2f73 |
completed | April 18, 2026, 4:57 p.m. |
Created at: April 10, 2026, 5:29 a.m.