Triple

T10923429
Position Surface form Disambiguated ID Type / Status
Subject Friedrichshafen E258002 entity
Predicate twinnedWith P1072 FINISHED
Object Kikinda E640765 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: Kikinda | Statement: [Friedrichshafen, twinnedWith, Kikinda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kikinda
Context triple: [Friedrichshafen, twinnedWith, Kikinda]
  • A. Kikinda chosen
    Kikinda is a town and municipality in northern Serbia known as a regional center of the Banat area, with a strong agricultural base and notable cultural and historical heritage.
  • B. Kilyos
    Kilyos is a seaside neighborhood on the Black Sea coast of Istanbul, Turkey, known for its beaches and summer resorts.
  • C. Kopaska
    Kopaska is the Indonesian Navy’s elite frogman and special operations unit, specializing in underwater demolition, maritime sabotage, and counter-terrorism missions.
  • D. Kushnar
    Kushnar is an alternative written form or spelling variant of the name Kushner.
  • E. Krempna
    Krempna is a small village in southeastern Poland that serves as a gateway and service center for visitors to Magura National Park in the Low Beskid Mountains.
  • 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_69d6aa864ed88190818280ab6791d065 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7708e3fd881908da10f24a856364c completed April 9, 2026, 9:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69e23bcee80481909a9ec8a03bc5266d completed April 17, 2026, 1:55 p.m.
Created at: April 8, 2026, 9:22 p.m.