Triple

T17058080
Position Surface form Disambiguated ID Type / Status
Subject Marinkina Tower E413875 entity
Predicate hasView P854 FINISHED
Object old town of Kolomna E119163 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: old town of Kolomna | Statement: [Marinkina Tower, hasView, old town of Kolomna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: old town of Kolomna
Context triple: [Marinkina Tower, hasView, old town of Kolomna]
  • A. Kolomna chosen
    Kolomna is a historic Russian city southeast of Moscow, known for its well-preserved kremlin, medieval architecture, and traditional pastila confectionery.
  • B. Smolenskaya
    Smolenskaya is a Moscow Metro station on the Arbatsko–Pokrovskaya and Filyovskaya lines, located near the historic Arbat district.
  • C. City of Pskov
    The City of Pskov is a historic Russian city near the Estonian border, renowned for its medieval kremlin, ancient churches, and role as a major fortress and trading center in northwestern Russia.
  • D. Staraya Russa
    Staraya Russa is a historic town in northwestern Russia known for its medieval heritage and mineral spa resorts.
  • E. Suzdal
    Suzdal is one of Russia’s oldest and best-preserved historic towns, renowned for its medieval churches, monasteries, and traditional wooden architecture.
  • 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_69d886cde3d481908d4d01ba88ba7eb7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3db7b553c81908ec70ba0d0988710 completed April 18, 2026, 7:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a012349b2c88190a5c5e06a5cae1ac5 completed May 11, 2026, 12:31 a.m.
Created at: April 10, 2026, 5:34 a.m.