Triple

T13262975
Position Surface form Disambiguated ID Type / Status
Subject Bhatye Beach E315844 entity
Predicate nearbyCity P350 FINISHED
Object Ratnagiri E79536 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: Ratnagiri | Statement: [Bhatye Beach, nearbyCity, Ratnagiri]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ratnagiri
Context triple: [Bhatye Beach, nearbyCity, Ratnagiri]
  • A. Ratnagiri chosen
    Ratnagiri is a coastal city in Maharashtra, India, known for its Alphonso mangoes, historic forts, and scenic beaches along the Konkan coast.
  • B. Baramati
    Baramati is a town in the Pune district of Maharashtra, India, known as an agricultural and industrial hub with historical and political significance.
  • C. Sangli
    Sangli is a city in the Indian state of Maharashtra known for its fertile agricultural surroundings and prominence in sugar and turmeric production.
  • D. Hingoli
    Hingoli is a city in the Indian state of Maharashtra, known as an administrative and commercial center in the Marathwada region.
  • E. Warora
    Warora is a town in Maharashtra, India, known historically for its coal mining and industrial activities within the Chandrapur district.
  • 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_69d806b1d9ac8190852c5571d5bd5f0f completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9901b380881909e6520fbb6811084 completed April 11, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd46686c288190a51847f86785568a completed May 8, 2026, 2:11 a.m.
Created at: April 9, 2026, 9:25 p.m.