Triple

T14998711
Position Surface form Disambiguated ID Type / Status
Subject Chagga people E374025 entity
Predicate geographicDistribution P2178 FINISHED
Object Hai District E374020 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: Hai District | Statement: [Chagga people, geographicDistribution, Hai District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hai District
Context triple: [Chagga people, geographicDistribution, Hai District]
  • A. Hai District chosen
    Hai District is an administrative district in northern Tanzania situated within the Kilimanjaro Region, known for its proximity to Mount Kilimanjaro and its largely rural, agricultural communities.
  • B. Pai District
    Pai District is a mountainous rural district in northern Thailand known for its scenic landscapes, laid-back backpacker town of Pai, and popularity as an eco-tourism and cultural tourism destination.
  • C. Kaifu District
    Kaifu District is an urban administrative district of Changsha, the capital city of Hunan Province in south-central China.
  • D. Kuta District
    Kuta District is a popular coastal area in southern Bali, Indonesia, known for its busy tourist beaches, nightlife, and surf culture.
  • E. Chikan District
    Chikan District is an urban administrative district and central area of Zhanjiang City in Guangdong Province, China.
  • 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_69d85ccc84388190aa151e5173370c8d completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded71a5618819083ae96a79735ef98 completed April 15, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69feb7d956808190a3f17ef14c21d3af completed May 9, 2026, 4:28 a.m.
Created at: April 10, 2026, 2:54 a.m.