Triple

T14662674
Position Surface form Disambiguated ID Type / Status
Subject Wojciech Kilar E344283 entity
Predicate notableWork P4 FINISHED
Object Orawa E19565 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: Orawa | Statement: [Wojciech Kilar, notableWork, Orawa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orawa
Context triple: [Wojciech Kilar, notableWork, Orawa]
  • A. Orawa chosen
    Orawa is a historical and ethnographic region in southern Poland known for its distinctive highland culture, folklore, and traditional wooden architecture.
  • B. Ogawa
    Ogawa is a town in Saitama Prefecture, Japan, known for its traditional Japanese paper (washi) production and its role as a local transport hub.
  • C. Ogawa
    Ogawa is a serotype of the bacterium Vibrio cholerae O1, commonly associated with cholera outbreaks worldwide.
  • D. Yabu
    Yabu is a small city in northern Hyōgo Prefecture, Japan, known for its rural landscapes, hot springs, and access to mountainous outdoor recreation.
  • E. Orito
    Orito is a municipality and town located in the Putumayo Department of southwestern Colombia, known for its role in regional oil production and its position within the Amazonian foothills.
  • 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_69d822e283fc8190a0e4c235cf880052 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb54ae5ac81908cc69891f280e5f7 completed April 14, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdfb7c7df88190a4e551a12f6e8158 completed May 8, 2026, 3:04 p.m.
Created at: April 10, 2026, 1:27 a.m.