Triple

T1094172
Position Surface form Disambiguated ID Type / Status
Subject Varhadi E24233 entity
Predicate spokenInCity P8343 FINISHED
Object Akola E166095 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: Akola | Statement: [Varhadi, spokenInCity, Akola]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Akola
Context triple: [Varhadi, spokenInCity, Akola]
  • A. Akola chosen
    Akola is a major city in the Vidarbha region of Maharashtra, India, known as an important commercial and educational center.
  • B. Alirajpur
    Alirajpur is a town and district headquarters in western Madhya Pradesh, India, known for its predominantly tribal population and vibrant indigenous culture.
  • C. Ashoknagar
    Ashoknagar is a town and administrative district headquarters in the central Indian state of Madhya Pradesh, known for its agricultural economy and regional trade.
  • D. Hoshangabad
    Hoshangabad is a city in the Indian state of Madhya Pradesh, known for its location on the banks of the Narmada River and its agricultural and industrial activities.
  • E. Jalgaon
    Jalgaon is a city in northwestern Maharashtra, India, known as a major commercial center for banana production and trade.
  • 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_69a4940542308190ac2a0b1f730b7cfc completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4b99d1e8c81909cf1178d68d38885 completed March 1, 2026, 10:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad4680a04481909e828a70d7fb24ed completed March 8, 2026, 9:50 a.m.
Created at: March 1, 2026, 7:42 p.m.