Triple

T9912713
Position Surface form Disambiguated ID Type / Status
Subject Beixiu Lake E185784 entity
Predicate hasNameInEnglish P3437 FINISHED
Object Beixiu Lake E185784 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: Beixiu Lake | Statement: [Beixiu Lake, hasNameInEnglish, Beixiu Lake]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beixiu Lake
Context triple: [Beixiu Lake, hasNameInEnglish, Beixiu Lake]
  • A. Beixiu Lake chosen
    Beixiu Lake is a scenic body of water located within Yuexiu Park, a major urban park and tourist attraction in Guangzhou, China.
  • B. Lushui Lake
    Lushui Lake is a scenic freshwater lake and popular leisure destination in Xianning, known for its tranquil waters and surrounding natural landscapes.
  • C. Liuye Lake
    Liuye Lake is a scenic freshwater lake and popular leisure destination in Changde, Hunan Province, known for its natural beauty and recreational activities.
  • D. Qilu Lake
    Qilu Lake is a freshwater lake located near the city of Yuxi in Yunnan Province, southwestern China, known for its plateau wetland ecosystem.
  • E. Baofeng Lake
    Baofeng Lake is a picturesque mountain lake in China’s Wulingyuan area, known for its clear emerald waters, dramatic karst peaks, and popular boat tours.
  • 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_69ca829b45f481909040f7b99a1976ed completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb53a300481909d917e487d8aab56 completed April 2, 2026, 12:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69d20dcbf28c8190aa9f6a8be423670a completed April 5, 2026, 7:22 a.m.
Created at: March 30, 2026, 8:41 p.m.