Triple

T11206994
Position Surface form Disambiguated ID Type / Status
Subject Jiujiang E265194 entity
Predicate near P350 FINISHED
Object Lushan Mountain E205470 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: Lushan Mountain | Statement: [Jiujiang, near, Lushan Mountain]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lushan Mountain
Context triple: [Jiujiang, near, Lushan Mountain]
  • A. Lushan Mountain chosen
    Lushan Mountain is a famous scenic and cultural mountain area in southeastern China, renowned for its dramatic cliffs, misty landscapes, and historical significance as a UNESCO World Heritage Site.
  • B. Wuling Mountain
    Wuling Mountain is a prominent peak in northern China known as the highest summit of the Yan Mountains range.
  • C. Lao Mountain
    Lao Mountain is a prominent coastal mountain range in eastern China known for its granite peaks, Taoist temples, and scenic views over the Yellow Sea.
  • D. Jinyun Mountain
    Jinyun Mountain is a scenic, forested mountain area in Chongqing, China, known for its rich biodiversity, cool climate, and popular hiking and nature tourism.
  • E. Zao Mountains
    Zao Mountains is a volcanic mountain range in northeastern Japan known for its ski resorts, hot springs, and the crater lake Okama.
  • 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_69d6aac59460819089b9848b27f57848 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8d4eef88190a7f05bca82d919b9 completed April 9, 2026, 5:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4973a1b288190bacdf56f8d4977bd completed April 19, 2026, 8:50 a.m.
Created at: April 8, 2026, 9:30 p.m.