Triple

T7356452
Position Surface form Disambiguated ID Type / Status
Subject Diu E169638 entity
Predicate partOf P40 FINISHED
Object Diu district E169634 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: Diu district | Statement: [Diu, partOf, Diu district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Diu district
Context triple: [Diu, partOf, Diu district]
  • A. Diu district chosen
    Diu district is a coastal administrative district of India known for its former Portuguese colonial heritage, beaches, and historic fortifications.
  • B. Dausa district
    Dausa district is an administrative district in the Indian state of Rajasthan, known for its historical sites, rural landscapes, and proximity to Jaipur.
  • C. Saha District
    Saha District is an administrative district (gu) in the southwestern part of Busan, South Korea, known for its coastal areas and residential neighborhoods.
  • D. Duki District
    Duki District is an administrative district in Pakistan’s Balochistan province, situated within its predominantly Pashtun-inhabited region.
  • E. Pujehun District
    Pujehun District is an administrative district in the Southern Province of Sierra Leone, known for its predominantly Mende population and largely rural, agricultural communities.
  • 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_69c68a59f2288190877ca15c19b1e822 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f13a62e48190a2d1781a630aa9f0 completed March 27, 2026, 9:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7faa6a5d88190b969b7783edc67b7 completed March 28, 2026, 3:58 p.m.
Created at: March 27, 2026, 3:06 p.m.