Triple

T7705027
Position Surface form Disambiguated ID Type / Status
Subject Massacre of Vassy E174590 entity
Predicate locatedIn P40 FINISHED
Object Vassy E174590 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: Vassy | Statement: [Massacre of Vassy, locatedIn, Vassy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vassy
Context triple: [Massacre of Vassy, locatedIn, Vassy]
  • A. Vassy chosen
    Vassy is a commune in northeastern France historically known as the site of the 1562 Massacre of Vassy, an event that helped ignite the French Wars of Religion.
  • B. Kin Vassy
    Kin Vassy was an American singer and songwriter best known for his work in country and pop music, including collaborations with artists like Kenny Rogers and Frank Zappa.
  • C. Aloysya
    Aloysya is a given name, typically a feminine variant of Aloysius, used in various cultures and languages.
  • D. Vika
    Vika is a central neighborhood in Oslo, Norway, known for its waterfront location, cultural institutions, and proximity to the city’s business district.
  • E. Antoshka
    Antoshka is a common Russian diminutive form of the male given name Anton, often used affectionately or informally.
  • 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_69c6995b3e8c8190833108f883d5f53c completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7028d72708190a8c8aa94a7ec905b completed March 27, 2026, 10:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8acc088148190ba5ba07e4ad2284c completed March 29, 2026, 4:38 a.m.
Created at: March 27, 2026, 4:03 p.m.