Triple

T2628454
Position Surface form Disambiguated ID Type / Status
Subject Dila Gori E59175 entity
Predicate shortName P43 FINISHED
Object Dila Gori E59175 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: Dila Gori | Statement: [Dila Gori, shortName, Dila Gori]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dila Gori
Context triple: [Dila Gori, shortName, Dila Gori]
  • A. Dila Gori chosen
    Dila Gori is a professional football club based in Gori, Georgia, competing in the country’s top-tier league.
  • B. Kharagauli
    Kharagauli is a small town in western Georgia known as a gateway to the Borjomi-Kharagauli National Park and as a local transport and administrative hub.
  • C. Baghat
    Baghat was a small princely state in colonial India that was incorporated into British-controlled territory during the 19th century.
  • D. Titagarh
    Titagarh is an industrial town in the North 24 Parganas district of eastern India, known historically for its jute mills and proximity to Kolkata.
  • E. Bomdila
    Bomdila is a hill town in northeastern India known for its Buddhist monasteries, scenic Himalayan views, and role as a cultural and administrative center in the region.
  • 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_69ab4ac558388190962492cd2e1b0ce6 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd8c2e3d88190a972f58356f282cc completed March 7, 2026, 7:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69af98b93a108190b21f4af3e8c16c2b completed March 10, 2026, 4:06 a.m.
Created at: March 6, 2026, 9:50 p.m.