Triple

T17592497
Position Surface form Disambiguated ID Type / Status
Subject Mulam E428480 entity
Predicate culturalRegion P1968 FINISHED
Object Guangxi NE NERFINISHED

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: Guangxi | Statement: [Mulam, culturalRegion, Guangxi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guangxi
Context triple: [Mulam, culturalRegion, Guangxi]
  • A. Guangxi Province chosen
    Guangxi Province is an autonomous region in southern China known for its ethnically diverse population, karst landscapes, and strategic location bordering Vietnam.
  • B. Xiangkhouang Province
    Xiangkhouang Province is a mountainous region in northeastern Laos known for its war history, cool climate, and the mysterious megalithic Plain of Jars archaeological landscape.
  • C. Guangdong Province
    Guangdong Province is a populous and economically vital coastal region in southern China, known for major cities like Guangzhou and Shenzhen and its role as a manufacturing and trade hub.
  • D. Guizhou Province
    Guizhou Province is a mountainous, ethnically diverse region in southwest China known for its karst landscapes, cool climate, and rapid economic development.
  • E. Bié Province
    Bié Province is a central Angolan province known for its highland terrain, agricultural activity, and strategic location bordering several other provinces.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889e1030481909950e140c63255b9 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e469e79dac8190953a1ce8fc015b20 completed April 19, 2026, 5:36 a.m.
Created at: April 10, 2026, 5:51 a.m.