Triple

T8932906
Position Surface form Disambiguated ID Type / Status
Subject Bong County E212699 entity
Predicate contains P35 FINISHED
Object Bong Range E771188 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: Bong Range | Statement: [Bong County, contains, Bong Range]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bong Range
Context triple: [Bong County, contains, Bong Range]
  • A. Bong Range chosen
    Bong Range is a mountain range in central Liberia known for its rich iron ore deposits and role in the region’s mining industry.
  • B. Nakawan Range
    Nakawan Range is a limestone mountain range forming part of the natural border between Malaysia and Thailand, known for its karst landscapes and biodiversity.
  • C. Kiso Range
    The Kiso Range is a mountain range in central Japan, forming part of the Japanese Alps and known for its steep, forested peaks and scenic hiking routes.
  • D. Tahan Range
    The Tahan Range is a mountainous region in Peninsular Malaysia known for its rugged terrain, dense rainforest, and status as part of Taman Negara National Park.
  • E. Atharamura Range
    Atharamura Range is a prominent hill range in the Indian state of Tripura, known for its forested terrain and role in shaping the region’s landscape and climate.
  • 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_69ca8395c438819087d7cb844ab5990c completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc668e5c108190b08f9cd6b4fd4a8b completed April 1, 2026, 12:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfdb856560819085132abe9ef94819 completed April 3, 2026, 3:23 p.m.
Created at: March 30, 2026, 6:57 p.m.