Triple

T8593861
Position Surface form Disambiguated ID Type / Status
Subject Southern Tour of 1992 E203495 entity
Predicate alsoKnownAs P39 FINISHED
Object nanxun
Nanxun refers to Deng Xiaoping’s influential 1992 “Southern Tour,” during which he revitalized China’s economic reform and opening-up policies through a series of speeches and inspections in southern cities.
 E745295 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: nanxun | Statement: [Southern Tour of 1992, alsoKnownAs, nanxun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: nanxun
Context triple: [Southern Tour of 1992, alsoKnownAs, nanxun]
  • A. NAX
    NAX is the ICAO airline designator used for Norwegian Air Shuttle, a major low-cost carrier based in Norway.
  • B. nan
    nan is the ISO 639-3 language code assigned to the Teochew (Chaoshan) Chinese language variety spoken primarily in eastern Guangdong, China, and among overseas Chinese communities.
  • C. NAN
    NAN is the three-letter IATA airport code for Nadi International Airport in Fiji.
  • D. NUAN
    NUAN is the stock ticker symbol for Nuance Communications, a company known for its speech recognition and conversational AI technologies.
  • E. N
    The N is a New York City Subway service that runs along the Broadway Line in Manhattan and connects Queens, Manhattan, and Brooklyn.
  • 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: nanxun
Triple: [Southern Tour of 1992, alsoKnownAs, nanxun]
Generated description
Nanxun refers to Deng Xiaoping’s influential 1992 “Southern Tour,” during which he revitalized China’s economic reform and opening-up policies through a series of speeches and inspections in southern cities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: nanxun
Target entity description: Nanxun refers to Deng Xiaoping’s influential 1992 “Southern Tour,” during which he revitalized China’s economic reform and opening-up policies through a series of speeches and inspections in southern cities.
  • A. NAX
    NAX is the ICAO airline designator used for Norwegian Air Shuttle, a major low-cost carrier based in Norway.
  • B. nan
    nan is the ISO 639-3 language code assigned to the Teochew (Chaoshan) Chinese language variety spoken primarily in eastern Guangdong, China, and among overseas Chinese communities.
  • C. NAN
    NAN is the three-letter IATA airport code for Nadi International Airport in Fiji.
  • D. NUAN
    NUAN is the stock ticker symbol for Nuance Communications, a company known for its speech recognition and conversational AI technologies.
  • E. N
    The N is a New York City Subway service that runs along the Broadway Line in Manhattan and connects Queens, Manhattan, and Brooklyn.
  • 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_69ca832a7f108190b4e4f5648abf4aa2 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc46c5e8888190b721e791c449b0df completed March 31, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea8becbd88190837478e302d5e5b4 completed April 2, 2026, 5:34 p.m.
NEDg Description generation batch_69cea9e685388190a4be9d2135dc02d0 completed April 2, 2026, 5:39 p.m.
NED2 Entity disambiguation (via description) batch_69ceaababe2c8190bc47430d33bfdbaa completed April 2, 2026, 5:43 p.m.
Created at: March 30, 2026, 6:23 p.m.