Triple

T19815001
Position Surface form Disambiguated ID Type / Status
Subject Kamareddy E476036 entity
Predicate hasRoadConnectivityWith P11435 FINISHED
Object Nanded 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: Nanded | Statement: [Kamareddy, hasRoadConnectivityWith, Nanded]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nanded
Context triple: [Kamareddy, hasRoadConnectivityWith, Nanded]
  • A. Nanded chosen
    Nanded is a historic city in the Indian state of Maharashtra, known as an important Sikh pilgrimage center and a major urban hub in the Marathwada region.
  • B. Latur
    Latur is a city in the Marathwada region of western India known for its agricultural economy and for being the epicenter of a devastating earthquake in 1993.
  • C. Gondia
    Gondia is a district in the Indian state of Maharashtra, known for its rice production and proximity to forests and wildlife reserves.
  • D. Paithan
    Paithan is an ancient town in Maharashtra, India, historically significant as a major political and cultural center of the Satavahana dynasty.
  • E. Sangli
    Sangli is a city in the Indian state of Maharashtra known for its fertile agricultural surroundings and prominence in sugar and turmeric production.
  • 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_69d8e51bc4208190a1c57d8c5d1b15e4 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e654f861248190a633dd8d227d9697 completed April 20, 2026, 4:31 p.m.
Created at: April 10, 2026, 1:50 p.m.