Triple

T14134846
Position Surface form Disambiguated ID Type / Status
Subject Teviotdale E350263 entity
Predicate hasTributaryRiver P415 FINISHED
Object Rule Water E615188 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: Rule Water | Statement: [Teviotdale, hasTributaryRiver, Rule Water]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rule Water
Context triple: [Teviotdale, hasTributaryRiver, Rule Water]
  • A. Rule Water chosen
    Rule Water is a river in the Scottish Borders that flows through rural Roxburghshire before joining the River Teviot.
  • B. Division of Water
    The Division of Water is a specialized unit within New York State’s environmental agency responsible for managing, protecting, and regulating the state’s water resources.
  • C. Division of Water
    The Division of Water is a unit within the Indiana Department of Natural Resources responsible for managing the state’s water resources, including floodplain management, water rights, and hydrologic monitoring.
  • D. Water
    Water is a fundamental chemical substance (H₂O) essential for life, known for its roles in biological processes, climate regulation, and human civilization.
  • E. Water
    Water is a 2005 Canadian-Indian drama film by Deepa Mehta that explores the lives and struggles of Hindu widows in 1930s colonial India.
  • 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_69d827865f608190b311820428ae027b completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de610e949c8190852d336c9d12bfd0 completed April 14, 2026, 3:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcdf14439c81908b2a9999a35cc346 completed May 7, 2026, 6:51 p.m.
Created at: April 9, 2026, 11:57 p.m.