Triple

T572148
Position Surface form Disambiguated ID Type / Status
Subject Leonid Brezhnev E13685 entity
Predicate placeOfBirth P1 FINISHED
Object Kamyanske E38828 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: Kamyanske | Statement: [Leonid Brezhnev, placeOfBirth, Kamyanske]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kamyanske
Context triple: [Leonid Brezhnev, placeOfBirth, Kamyanske]
  • A. Kievskaya
    Kievskaya is a prominent Moscow Metro station complex known for its ornate, Ukrainian-themed architecture and role as a major transfer hub.
  • B. Zhytomyr
    Zhytomyr is a historic city in northwestern Ukraine known as an important regional center and the birthplace of pioneering rocket engineer Sergei Korolev.
  • C. Lutsk
    Lutsk is a historic city in northwestern Ukraine, known as the administrative center of Volyn Oblast and one of the region’s oldest cultural and economic hubs.
  • D. Novoslobodskaya
    Novoslobodskaya is a Moscow Metro station famed for its distinctive stained-glass panels and ornate, cathedral-like interior design.
  • E. Dnipro chosen
    Dnipro is one of Ukraine’s largest industrial and cultural centers, located on the Dnieper River in the central-eastern part of the country.
  • 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_69a4933fa4d88190a7949cc83c08c5c1 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49b49bad88190bc73d31a317c0ef4 completed March 1, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69a50e23bce481908404040b848ba9c1 completed March 2, 2026, 4:12 a.m.
Created at: March 1, 2026, 7:33 p.m.