Triple
T16109434
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temryuksky District |
E390833
|
entity |
| Predicate | administrativeCenter |
P1474
|
FINISHED |
| Object | Temryuk |
E962654
|
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: Temryuk | Statement: [Temryuksky District, administrativeCenter, Temryuk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Temryuk Context triple: [Temryuksky District, administrativeCenter, Temryuk]
-
A.
Temryuk
chosen
Temryuk is a town in Russia’s Krasnodar Krai, known as a port and regional center near the Sea of Azov.
-
B.
Yura
Yura is a common Slavic diminutive form of the male given name Yuri (or Yuriy), often used as a familiar or affectionate nickname.
-
C.
Yakut
Yakut is a Turkic language spoken primarily in the Sakha Republic (Yakutia) in northeastern Siberia, Russia.
-
D.
Amursk
Amursk is a small industrial town in Russia’s Far East, situated on the Amur River and known for its timber and pulp-and-paper industries.
-
E.
Taihe
Taihe was a historical Chinese era name used during the Three Kingdoms period under the state of Cao Wei.
- 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_69d87f1a8dd881909f1de6ef78849874 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2016665c0819081aa7a44b1d08183 |
completed | April 17, 2026, 9:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffeba674788190a589104cf90f28d5 |
completed | May 10, 2026, 2:21 a.m. |
Created at: April 10, 2026, 5 a.m.