Triple

T8294530
Position Surface form Disambiguated ID Type / Status
Subject Guntur district E194180 entity
Predicate hasTown P847 FINISHED
Object Mangalagiri E748197 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: Mangalagiri | Statement: [Guntur district, hasTown, Mangalagiri]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mangalagiri
Context triple: [Guntur district, hasTown, Mangalagiri]
  • A. Mangalagiri chosen
    Mangalagiri is a town in Andhra Pradesh, India, known for its historic temples and traditional handloom weaving.
  • B. Puttaparthi
    Puttaparthi is a renowned spiritual town in Andhra Pradesh, India, best known as the birthplace and ashram site of the guru Sathya Sai Baba.
  • C. Tirumala
    Tirumala is a prominent hill town in Andhra Pradesh, India, best known as the site of the revered Tirumala Venkateswara Temple, one of Hinduism’s most important pilgrimage destinations.
  • D. Chandragiri
    Chandragiri is a historic town in Andhra Pradesh, India, known for its ancient fort and former role as a capital of the Vijayanagara Empire.
  • E. Allagadda
    Allagadda is a town and legislative assembly constituency in the Nandyal district of Andhra Pradesh, India.
  • 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_69ca82e50ebc81909aa7b260c76bd757 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7df5fff88190ac51a8d1c3eb2fe2 completed March 31, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69cef2d359208190bdeb494e090920ea completed April 2, 2026, 10:50 p.m.
Created at: March 30, 2026, 5:52 p.m.