Triple

T11976586
Position Surface form Disambiguated ID Type / Status
Subject Dausa district E285055 entity
Predicate hasTown P847 FINISHED
Object Bandikui
Bandikui is a railway junction town in Rajasthan, India, historically significant as one of the earliest and most important railway hubs in the region.
 E957927 NE FINISHED

How this triple was built (4 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: Bandikui | Statement: [Dausa district, hasTown, Bandikui]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bandikui
Context triple: [Dausa district, hasTown, Bandikui]
  • A. Yachimun
    Yachimun is the traditional Okinawan pottery style known for its rustic forms, vivid glazes, and deep roots in Ryukyuan culture and craftsmanship.
  • B. Munji
    Munji is a lesser-known Eastern Iranian language spoken by the Munji people in the remote Munjan Valley of northeastern Afghanistan.
  • C. Kutama
    Kutama is a rural village in the Zvimba District of northern Zimbabwe, known primarily as the birthplace of former president Robert Mugabe.
  • D. Kimpo
    Kimpo is the former romanized spelling of Gimpo, a city in Gyeonggi Province, South Korea, known for its proximity to Seoul and its international airport.
  • E. Kasagi
    Kasagi is a small town in Kyoto Prefecture, Japan, known for its scenic river landscapes and historic temples.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Bandikui
Triple: [Dausa district, hasTown, Bandikui]
Generated description
Bandikui is a railway junction town in Rajasthan, India, historically significant as one of the earliest and most important railway hubs in the region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bandikui
Target entity description: Bandikui is a railway junction town in Rajasthan, India, historically significant as one of the earliest and most important railway hubs in the region.
  • A. Yachimun
    Yachimun is the traditional Okinawan pottery style known for its rustic forms, vivid glazes, and deep roots in Ryukyuan culture and craftsmanship.
  • B. Munji
    Munji is a lesser-known Eastern Iranian language spoken by the Munji people in the remote Munjan Valley of northeastern Afghanistan.
  • C. Kutama
    Kutama is a rural village in the Zvimba District of northern Zimbabwe, known primarily as the birthplace of former president Robert Mugabe.
  • D. Kimpo
    Kimpo is the former romanized spelling of Gimpo, a city in Gyeonggi Province, South Korea, known for its proximity to Seoul and its international airport.
  • E. Kasagi
    Kasagi is a small town in Kyoto Prefecture, Japan, known for its scenic river landscapes and historic temples.
  • F. None of above. chosen

Provenance (5 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_69d6ab2eaeb881909f7914758f859413 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903926690819090e7ce982f103457 completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f471f6afc48190856a0f7c486b28aa completed May 1, 2026, 9:27 a.m.
NEDg Description generation batch_69f47b7ac4048190ae09f18f1a90338f completed May 1, 2026, 10:07 a.m.
NED2 Entity disambiguation (via description) batch_69f47db91f38819092b7b5c5e2bb489b completed May 1, 2026, 10:17 a.m.
Created at: April 8, 2026, 9:46 p.m.