Triple

T13555789
Position Surface form Disambiguated ID Type / Status
Subject Bhagwati Fort E323769 entity
Predicate locatedNear P294 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: [Bhagwati Fort, locatedNear, Ratnagiri]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ratnagiri
Context triple: [Bhagwati Fort, locatedNear, 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_69d8076830b48190910a902bae5888e2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaff3063c8190bd20149b3f7df352 completed April 12, 2026, 2:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe729a48288190bf24503af6522677 completed May 8, 2026, 11:32 p.m.
Created at: April 9, 2026, 9:47 p.m.