Triple

T12310087
Position Surface form Disambiguated ID Type / Status
Subject Pune district E293453 entity
Predicate containsTown P847 FINISHED
Object Baramati E28220 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: Baramati | Statement: [Pune district, containsTown, Baramati]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baramati
Context triple: [Pune district, containsTown, Baramati]
  • A. Baramati chosen
    Baramati is a town in the Pune district of Maharashtra, India, known as an agricultural and industrial hub with historical and political significance.
  • B. Warora
    Warora is a town in Maharashtra, India, known historically for its coal mining and industrial activities within the Chandrapur district.
  • C. Bhusawal
    Bhusawal is a major railway and commercial city in Maharashtra, India, known for its large railway junction and banana-growing region.
  • D. Malegaon
    Malegaon is a major textile and powerloom town in Maharashtra, India, known for its large Muslim population and vibrant weaving industry.
  • E. Ulhasnagar
    Ulhasnagar is a city in the Mumbai Metropolitan Region of Maharashtra, India, known for its large Sindhi community and extensive furniture and textile markets.
  • 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_69d6ab6a2b50819082f6aedd32ed608a completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f02c0508190b10c0627cdaaba76 completed April 10, 2026, 6:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69f634688f548190b3c9013591da939b completed May 2, 2026, 5:29 p.m.
Created at: April 8, 2026, 9:53 p.m.