Triple

T13152363
Position Surface form Disambiguated ID Type / Status
Subject Minden, Germany E312496 entity
Predicate twinTown P1072 FINISHED
Object Syktyvkar, Russia E309974 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: Syktyvkar, Russia | Statement: [Minden, Germany, twinTown, Syktyvkar, Russia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Syktyvkar, Russia
Context triple: [Minden, Germany, twinTown, Syktyvkar, Russia]
  • A. Syktyvkar chosen
    Syktyvkar is the capital city of the Komi Republic in northwestern Russia, known as an administrative, cultural, and economic center of the region.
  • B. Karaganda
    Karaganda is a large industrial city in central Kazakhstan known for its coal mining industry and Soviet-era history.
  • C. Kaspiysk
    Kaspiysk is a coastal city on the Caspian Sea in the Republic of Dagestan, Russia, known for its industrial base and strategic naval facilities.
  • D. Irkutsk, Russia
    Irkutsk, Russia is a historic Siberian city near Lake Baikal known for its role as a cultural and educational center in eastern Russia.
  • E. Kokshetau
    Kokshetau is a city in northern Kazakhstan that serves as the administrative and economic center of the surrounding Akmola Region.
  • 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_69d806aabde48190899e13e41659cae5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98bd317e0819086e383f8e4583630 completed April 10, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcf7cb4d348190962ba5fa21fbb77b completed May 7, 2026, 8:36 p.m.
Created at: April 9, 2026, 9:11 p.m.