Triple

T1671703
Position Surface form Disambiguated ID Type / Status
Subject Shanghai Stock Exchange E36138 entity
Predicate abbreviation P43 FINISHED
Object SSE
SSE is the commonly used abbreviation for the Shanghai Stock Exchange, one of the largest stock exchanges in the world and a major financial hub in China.
 E190328 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: SSE | Statement: [Shanghai Stock Exchange, abbreviation, SSE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SSE
Context triple: [Shanghai Stock Exchange, abbreviation, SSE]
  • A. SSE
    SSE is the abbreviation for the Santiago Stock Exchange, the main securities exchange in Chile.
  • B. SST
    SST is the standard time observed in American Samoa, corresponding to the Samoa Time Zone.
  • C. SSE2
    SSE2 is an x86 processor instruction set extension introduced by Intel that adds advanced SIMD (Single Instruction, Multiple Data) capabilities for faster floating-point and integer computations.
  • D. SSS
    SSS is the commonly used abbreviation for the Selective Service System, the U.S. government agency that maintains information on individuals potentially subject to military conscription.
  • E. SAS
    SAS is an elite special forces unit of the British Army renowned for its covert operations, counterterrorism expertise, and rigorous selection process.
  • 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: SSE
Triple: [Shanghai Stock Exchange, abbreviation, SSE]
Generated description
SSE is the commonly used abbreviation for the Shanghai Stock Exchange, one of the largest stock exchanges in the world and a major financial hub in China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SSE
Target entity description: SSE is the commonly used abbreviation for the Shanghai Stock Exchange, one of the largest stock exchanges in the world and a major financial hub in China.
  • A. SSE
    SSE is the abbreviation for the Santiago Stock Exchange, the main securities exchange in Chile.
  • B. SST
    SST is the standard time observed in American Samoa, corresponding to the Samoa Time Zone.
  • C. SSE2
    SSE2 is an x86 processor instruction set extension introduced by Intel that adds advanced SIMD (Single Instruction, Multiple Data) capabilities for faster floating-point and integer computations.
  • D. SSS
    SSS is the commonly used abbreviation for the Selective Service System, the U.S. government agency that maintains information on individuals potentially subject to military conscription.
  • E. SAS
    SAS is a widely used statistical software suite for advanced analytics, business intelligence, data management, and predictive modeling.
  • 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_69a8861286808190939afff3ce8ee31e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa62439e48819084e46b2719cdac58 completed March 6, 2026, 5:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad71b0cde08190a210cf387459e9ad completed March 8, 2026, 12:55 p.m.
NEDg Description generation batch_69ad73e42340819092ef5ee85e3f7b7f completed March 8, 2026, 1:04 p.m.
NED2 Entity disambiguation (via description) batch_69ad7464fe9c8190a98d8e98129c61c0 completed March 8, 2026, 1:06 p.m.
Created at: March 4, 2026, 7:29 p.m.