Triple

T3267787
Position Surface form Disambiguated ID Type / Status
Subject arrondissement of Gex E68567 entity
Predicate containsAdministrativeTerritorialEntity P747 FINISHED
Object Sergy E89751 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: Sergy | Statement: [arrondissement of Gex, containsAdministrativeTerritorialEntity, Sergy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sergy
Context triple: [arrondissement of Gex, containsAdministrativeTerritorialEntity, Sergy]
  • A. Sergy chosen
    Sergy is a small commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
  • B. Sergei
    Sergei is a masculine given name of Slavic origin, commonly used in Russia and other Eastern European countries.
  • C. Vasilevsky
    Vasilevsky is a Russian surname most prominently associated with Aleksandr Vasilevsky, a leading Soviet military commander and Marshal of the Soviet Union during World War II.
  • D. Serge
    Serge is a masculine given name of French origin, commonly used in Francophone countries and derived from the Latin name Sergius.
  • E. Sergiy
    Sergiy is a given name, commonly used as a Ukrainian or Eastern European variant of the name Sergei.
  • 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_69ad8590444081909e8107a8aeef3a23 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adafcf9c6c819092f9c618b778b46d completed March 8, 2026, 5:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69b28ef261ec819091c62620765e2cef completed March 12, 2026, 10:01 a.m.
Created at: March 8, 2026, 3:09 p.m.