Triple

T7446267
Position Surface form Disambiguated ID Type / Status
Subject Baotou E171888 entity
Predicate ChineseName P744 FINISHED
Object 包头 E171888 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: 包头 | Statement: [Baotou, ChineseName, 包头]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 包头
Context triple: [Baotou, ChineseName, 包头]
  • A. Baotou chosen
    Baotou is a major industrial city in Inner Mongolia, China, known especially for its steel production and nearby rare earth mineral processing.
  • B. Chifeng
    Chifeng is a prefecture-level city in southeastern Inner Mongolia, China, known for its mix of grassland, forest, and historical sites linked to ancient nomadic cultures.
  • C. Hohhot
    Hohhot is the capital and largest city of Inner Mongolia in northern China, known as a regional center of politics, culture, and industry.
  • D. Wuhai
    Wuhai is a prefecture-level industrial city in western Inner Mongolia, China, known for its coal mining, chemical industries, and location along the Yellow River.
  • E. Baoding
    Baoding is a historic prefecture-level city in central Hebei Province, China, known as a regional transportation hub and former military and administrative center.
  • 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_69c68a65402881908f7869368eb746fb completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f371be2081908feaeb9392cb65fe completed March 27, 2026, 9:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c827a6668c8190a88c6406684e7689 completed March 28, 2026, 7:10 p.m.
Created at: March 27, 2026, 3:14 p.m.