Triple

T3331950
Position Surface form Disambiguated ID Type / Status
Subject Khabarovsk Krai E70051 entity
Predicate hasPart P35 FINISHED
Object 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.
 E348040 NE FINISHED

How this triple was built (4 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: Amursk | Statement: [Khabarovsk Krai, hasPart, Amursk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Amursk
Context triple: [Khabarovsk Krai, hasPart, Amursk]
  • A. Chita
    Chita is a city in southeastern Siberia, Russia, serving as an important administrative, cultural, and transportation center of Zabaykalsky Krai.
  • B. Komsomolsk-on-Amur
    Komsomolsk-on-Amur is a major industrial city in Russia’s Khabarovsk Krai, known for its shipbuilding and aircraft manufacturing industries in the Russian Far East.
  • C. Komsomolskaya
    Komsomolskaya is one of Moscow Metro’s most famous and ornate stations, renowned for its grand Baroque-style decor and elaborate mosaics.
  • D. Rizhskaya
    Rizhskaya is a Moscow Metro station on the Big Circle Line serving the Rizhsky railway terminal area.
  • E. Yura
    Yura is a common Slavic diminutive form of the male given name Yuri (or Yuriy), often used as a familiar or affectionate nickname.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Amursk
Triple: [Khabarovsk Krai, hasPart, Amursk]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Amursk
Target entity description: 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.
  • A. Chita
    Chita is a city in southeastern Siberia, Russia, serving as an important administrative, cultural, and transportation center of Zabaykalsky Krai.
  • B. Komsomolsk-on-Amur
    Komsomolsk-on-Amur is a major industrial city in Russia’s Khabarovsk Krai, known for its shipbuilding and aircraft manufacturing industries in the Russian Far East.
  • C. Komsomolskaya
    Komsomolskaya is one of Moscow Metro’s most famous and ornate stations, renowned for its grand Baroque-style decor and elaborate mosaics.
  • D. Rizhskaya
    Rizhskaya is a Moscow Metro station on the Big Circle Line serving the Rizhsky railway terminal area.
  • E. Yura
    Yura is a common Slavic diminutive form of the male given name Yuri (or Yuriy), often used as a familiar or affectionate nickname.
  • F. None of above. chosen

Provenance (5 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_69ad85a24f208190bcf83131bfed3521 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb19358e48190a503af01b92273a4 completed March 8, 2026, 5:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69b31a841c608190942e040c14f560d2 completed March 12, 2026, 7:56 p.m.
NEDg Description generation batch_69b31c37f3a08190823c32e8f933ce82 completed March 12, 2026, 8:04 p.m.
NED2 Entity disambiguation (via description) batch_69b31caa4e188190b4dfd613fdaebdb6 completed March 12, 2026, 8:06 p.m.
Created at: March 8, 2026, 3:12 p.m.