Triple

T4283323
Position Surface form Disambiguated ID Type / Status
Subject Quanzhou E97206 entity
Predicate hasCountyLevelCity P27799 FINISHED
Object Shishi
Shishi is a coastal county-level city in Fujian Province, China, known as a major center for the textile and garment industry.
 E426394 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: Shishi | Statement: [Quanzhou, hasCountyLevelCity, Shishi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Shishi
Context triple: [Quanzhou, hasCountyLevelCity, Shishi]
  • A. Shichahai
    Shichahai is a historic scenic area in central Beijing known for its interconnected lakes, traditional hutong neighborhoods, and vibrant cultural and leisure activities.
  • B. Taishi
    Taishi is a town in Osaka Prefecture, Japan, known for its historical sites and traditional rural character.
  • C. Shi
    Shi is a Chinese surname historically associated with members of the Jewish community in Kaifeng, China.
  • D. Rinshunkaku
    Rinshunkaku is a historic Japanese-style pavilion located within Yokohama’s Sankeien Garden, known for its traditional architecture and scenic setting.
  • E. Tsu
    Tsu is a coastal city in central Japan that serves as the administrative and economic center of Mie Prefecture.
  • 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: Shishi
Triple: [Quanzhou, hasCountyLevelCity, Shishi]
Generated description
Shishi is a coastal county-level city in Fujian Province, China, known as a major center for the textile and garment industry.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Shishi
Target entity description: Shishi is a coastal county-level city in Fujian Province, China, known as a major center for the textile and garment industry.
  • A. Shichahai
    Shichahai is a historic scenic area in central Beijing known for its interconnected lakes, traditional hutong neighborhoods, and vibrant cultural and leisure activities.
  • B. Taishi
    Taishi is a town in Osaka Prefecture, Japan, known for its historical sites and traditional rural character.
  • C. Shi
    Shi is a Chinese surname historically associated with members of the Jewish community in Kaifeng, China.
  • D. Rinshunkaku
    Rinshunkaku is a historic Japanese-style pavilion located within Yokohama’s Sankeien Garden, known for its traditional architecture and scenic setting.
  • E. Tsu
    Tsu is a coastal city in central Japan that serves as the administrative and economic center of Mie Prefecture.
  • 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_69b3454595848190a0e6bbb6a2bea040 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3503a84548190989a96d1a30d6ef7 completed March 12, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b7bec1a88190bd36ed6d48e1c94e completed March 14, 2026, 7:32 p.m.
NEDg Description generation batch_69b5b870a66c8190a59bfc0e99234596 completed March 14, 2026, 7:35 p.m.
NED2 Entity disambiguation (via description) batch_69b5b908fad88190846278c782a10cdb completed March 14, 2026, 7:37 p.m.
Created at: March 12, 2026, 11:07 p.m.