Triple

T2236243
Position Surface form Disambiguated ID Type / Status
Subject Gora E49286 entity
Predicate adaptation P1964 FINISHED
Object Gora (television series) E49286 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: Gora (television series) | Statement: [Gora, adaptation, Gora (television series)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gora (television series)
Context triple: [Gora, adaptation, Gora (television series)]
  • A. Sama Gaun
    Sama Gaun is a remote Himalayan village in Nepal that serves as a key acclimatization and trekking stop on the Manaslu Circuit near Mount Manaslu.
  • B. Gora chosen
    Gora is a major Bengali novel by Rabindranath Tagore that explores themes of identity, nationalism, and religious and social reform in colonial India.
  • C. Ora TV
    Ora TV is a digital television network and production company co-founded by Larry King that creates and distributes original online video programming.
  • D. Görliwood
    Görliwood is the popular nickname for the German city of Görlitz, known as a frequent filming location for international movies and TV productions.
  • E. Gori
    Gori is a city in central Georgia best known as the birthplace of Soviet leader Joseph Stalin.
  • 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_69a88aa84bdc819086df50e9c20b301e completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc093ba0c819091df09a0e018fce1 completed March 7, 2026, 6:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6b08c5248190924a28f4c1bd0e2c completed March 9, 2026, 6:39 a.m.
Created at: March 4, 2026, 7:47 p.m.