Triple

T3610517
Position Surface form Disambiguated ID Type / Status
Subject Lanzhou E76473 entity
Predicate historicalName P65 FINISHED
Object Jincheng
Jincheng is an ancient name historically used for the Chinese city now known as Lanzhou, a key regional center along the Silk Road in Gansu Province.
 E378303 NE FINISHED

How this triple was built (4 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: Jincheng | Statement: [Lanzhou, historicalName, Jincheng]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jincheng
Context triple: [Lanzhou, historicalName, Jincheng]
  • A. Jincheng
    Jincheng is a prefecture-level city in southeastern Shanxi Province, China, known for its coal resources and heavy industry.
  • B. Yuncheng
    Yuncheng is a major city in southern Shanxi Province, China, known for its historical sites and role as a regional transportation and economic hub.
  • C. Lincang
    Lincang is a prefecture-level city in southwestern China known for its tea production, diverse ethnic cultures, and location near the border with Myanmar.
  • D. Datong
    Datong is a historic industrial city in northern China known for its coal production and nearby cultural landmarks such as the Yungang Grottoes.
  • E. Wu’an
    Wu’an is a county-level city administered by Handan in Hebei Province, northern China, known for its industrial development and coal resources.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Jincheng
Triple: [Lanzhou, historicalName, Jincheng]
Generated description
Jincheng is an ancient name historically used for the Chinese city now known as Lanzhou, a key regional center along the Silk Road in Gansu Province.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jincheng
Target entity description: Jincheng is an ancient name historically used for the Chinese city now known as Lanzhou, a key regional center along the Silk Road in Gansu Province.
  • A. Jincheng
    Jincheng is a prefecture-level city in southeastern Shanxi Province, China, known for its coal resources and heavy industry.
  • B. Yuncheng
    Yuncheng is a major city in southern Shanxi Province, China, known for its historical sites and role as a regional transportation and economic hub.
  • C. Lincang
    Lincang is a prefecture-level city in southwestern China known for its tea production, diverse ethnic cultures, and location near the border with Myanmar.
  • D. Datong
    Datong is a historic industrial city in northern China known for its coal production and nearby cultural landmarks such as the Yungang Grottoes.
  • E. Wu’an
    Wu’an is a county-level city administered by Handan in Hebei Province, northern China, known for its industrial development and coal resources.
  • F. None of above. chosen

Provenance (5 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_69ad85da0ba481908b3b48c69efe2b98 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc22cac3c8190bc5f7c45d31668c1 completed March 8, 2026, 6:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4882a556881909e6c20cce617e4b6 completed March 13, 2026, 9:56 p.m.
NEDg Description generation batch_69b48bd150088190a0ac0e2f9dafae85 completed March 13, 2026, 10:12 p.m.
NED2 Entity disambiguation (via description) batch_69b4b72f71bc8190a5cba6741db1e105 completed March 14, 2026, 1:17 a.m.
Created at: March 8, 2026, 3:23 p.m.