Triple

T23494615
Position Surface form Disambiguated ID Type / Status
Subject Ganjam district E571668 entity
Predicate hasTown P847 FINISHED
Object Chikiti NE NERFINISHED

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: Chikiti | Statement: [Ganjam district, hasTown, Chikiti]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chikiti
Context triple: [Ganjam district, hasTown, Chikiti]
  • A. Chikiti chosen
    Chikiti is a town in the Ganjam district of Odisha, India, known for its local markets and regional administrative significance.
  • B. Chikushino
    Chikushino is a city in southwestern Japan known as a residential and commercial hub within the Fukuoka metropolitan area.
  • C. Kachiun
    Kachiun was a Mongol prince and military commander, known as one of Genghis Khan’s loyal brothers who played a key role in the early Mongol conquests.
  • D. Tukuche
    Tukuche is a traditional Thakali village in Nepal’s Mustang region, known for its historic houses, apple orchards, and location along the Annapurna trekking route.
  • E. Chakiwara
    Chakiwara is a residential neighborhood located within Lyari Town in Karachi, Pakistan, known for its dense urban character and vibrant local culture.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245b4829881909b77a70e942bbd54 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a7def8ac8190ade511299078d55b completed April 29, 2026, 6:40 a.m.
Created at: April 17, 2026, 6:05 p.m.