Triple

T13281937
Position Surface form Disambiguated ID Type / Status
Subject Kita-Toda Station E316342 entity
Predicate servedArea P82 FINISHED
Object Toda E872938 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: Toda | Statement: [Kita-Toda Station, servedArea, Toda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toda
Context triple: [Kita-Toda Station, servedArea, Toda]
  • A. Toda
    Toda is a subgroup of the Seediq, an Indigenous people of Taiwan known for their distinct language and cultural traditions.
  • B. Toda
    Toda is a Southern Dravidian language spoken by the Toda people of the Nilgiri Hills in southern India, known for its highly complex phonology and small speaker population.
  • C. Toda chosen
    Toda is a city in Saitama Prefecture, Japan, located just north of Tokyo and known as a residential and commuter town in the Greater Tokyo Area.
  • D. Tiba
    Tiba is a modern planned city in Egypt’s Luxor Governorate, developed to accommodate population growth and support regional economic and urban expansion.
  • E. Eusa
    Eusa is the Breton name for Ushant, an island off the western tip of Brittany in France known for its rugged coastline and maritime heritage.
  • 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_69d806b349908190a9a61dd9323bf153 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9904507588190a303686d176ec3e1 completed April 11, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69f716cfea308190836eb4892e7c5eb4 completed May 3, 2026, 9:35 a.m.
Created at: April 9, 2026, 9:27 p.m.