Triple

T18562742
Position Surface form Disambiguated ID Type / Status
Subject Laoshan District, Qingdao E453685 entity
Predicate knownFor P22 FINISHED
Object Laoshan Mountain 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: Laoshan Mountain | Statement: [Laoshan District, Qingdao, knownFor, Laoshan Mountain]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laoshan Mountain
Context triple: [Laoshan District, Qingdao, knownFor, Laoshan Mountain]
  • A. Yantai Mountain
    Yantai Mountain is a historic coastal scenic area in Yantai, China, known for its lighthouse, old foreign consulates, and panoramic views of the Bohai Sea.
  • B. Laoshan Scenic Area chosen
    Laoshan Scenic Area is a famous coastal mountain tourist destination in Qingdao, China, known for its granite peaks, Taoist temples, and scenic views of the Yellow Sea.
  • C. Lingshan Mountain
    Lingshan Mountain is the highest peak in Beijing, known for its alpine meadows, diverse flora, and scenic hiking trails.
  • D. Xiaowutai Mountain
    Xiaowutai Mountain is the highest peak of the Taihang mountain range in northern China, known for its rugged terrain and alpine scenery.
  • E. Siming Mountains
    The Siming Mountains are a scenic mountain range in eastern Zhejiang Province, China, known for their lush forests, tea cultivation, and cultural heritage sites.
  • 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_69d8d38974308190a9174430ef256b73 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e53afb4f088190adf0b2b64057a210 completed April 19, 2026, 8:28 p.m.
Created at: April 10, 2026, 11:42 a.m.