Triple

T3323263
Position Surface form Disambiguated ID Type / Status
Subject John Howard E69847 entity
Predicate placeOfDeath P21 FINISHED
Object Kherson E279040 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: Kherson | Statement: [John Howard, placeOfDeath, Kherson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kherson
Context triple: [John Howard, placeOfDeath, Kherson]
  • A. Kherson chosen
    Kherson is a port city in southern Ukraine near the Black Sea, historically significant as a shipbuilding and industrial center and strategically important due to its location on the Dnieper River.
  • B. Mykolaiv
    Mykolaiv is a major shipbuilding and industrial city in southern Ukraine located near the Black Sea.
  • C. Odesa
    Odesa is a major port city on the Black Sea in southern Ukraine, known for its historic architecture, multicultural heritage, and key economic and cultural role in the country.
  • D. Odessa
    Odessa is a mid-sized city in western Texas known for its oil industry, high school football culture, and role in the Permian Basin energy region.
  • E. Kharkiv
    Kharkiv is Ukraine’s second-largest city and a major industrial, cultural, and educational center in the northeast 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_69ad85a1829881908942c14075644d0d completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb13e6c288190805f8abcd3acc906 completed March 8, 2026, 5:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69b503d6cd9c81908acb288091503ec1 completed March 14, 2026, 6:44 a.m.
Created at: March 8, 2026, 3:11 p.m.