Triple

T12291598
Position Surface form Disambiguated ID Type / Status
Subject Aa River E292976 entity
Predicate hasName P744 FINISHED
Object Aa River E292976 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: Aa River | Statement: [Aa River, hasName, Aa River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aa River
Context triple: [Aa River, hasName, Aa River]
  • A. Aa River chosen
    The Aa River is a waterway in northern France that flows through the town of Saint-Omer before emptying into the North Sea.
  • B. Geum River
    The Geum River is a major river in western South Korea that flows through the central region before emptying into the Yellow Sea.
  • C. Harangi River
    The Harangi River is a tributary of the Kaveri River in Karnataka, India, known for the Harangi Dam that supports irrigation and regional water management.
  • D. Sangkae River
    The Sangkae River is a key waterway in northwestern Cambodia that flows through and sustains the city of Battambang and its surrounding agricultural areas.
  • E. Bara River
    The Bara River is a tributary of the Kabul River flowing through the Khyber Pakhtunkhwa region of Pakistan, passing near the city of Peshawar.
  • 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_69d6ab690ad081908c0ed3870ec82d53 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91d22ba488190914342fa7e69e159 completed April 10, 2026, 3:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7ce593bbc8190827ca217f43140b9 completed May 3, 2026, 10:38 p.m.
Created at: April 8, 2026, 9:52 p.m.