Triple

T478702
Position Surface form Disambiguated ID Type / Status
Subject Santiago Stock Exchange E9117 entity
Predicate hasAbbreviation P43 FINISHED
Object SSE
SSE is the abbreviation for the Santiago Stock Exchange, the main securities exchange in Chile.
 E59994 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: [Santiago Stock Exchange, hasAbbreviation, SSE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SSE
Context triple: [Santiago Stock Exchange, hasAbbreviation, SSE]
  • A. 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.
  • B. SAS
    SAS is an elite special forces unit of the British Army renowned for its covert operations, counterterrorism expertise, and rigorous selection process.
  • C. SAS
    SAS is a widely used statistical software suite for advanced analytics, business intelligence, data management, and predictive modeling.
  • D. SAS
    SAS is a high-speed, point-to-point serial interface standard commonly used to connect enterprise storage devices like hard drives and solid-state drives to servers.
  • E. SAS
    SAS is the School of Arts and Sciences at the University of Pennsylvania, encompassing the university’s core liberal arts and sciences departments and programs.
  • 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: [Santiago Stock Exchange, hasAbbreviation, SSE]
Generated description
SSE is the abbreviation for the Santiago Stock Exchange, the main securities exchange in Chile.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SSE
Target entity description: SSE is the abbreviation for the Santiago Stock Exchange, the main securities exchange in Chile.
  • A. 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.
  • B. SAS
    SAS is a widely used statistical software suite for advanced analytics, business intelligence, data management, and predictive modeling.
  • C. SAS
    SAS is an elite special forces unit of the British Army renowned for its covert operations, counterterrorism expertise, and rigorous selection process.
  • D. SAS
    SAS is a high-speed, point-to-point serial interface standard commonly used to connect enterprise storage devices like hard drives and solid-state drives to servers.
  • E. SAS
    SAS is the School of Arts and Sciences at the University of Pennsylvania, encompassing the university’s core liberal arts and sciences departments and programs.
  • 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_69a2e7ff81708190b0507a24a997232c completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2f056459881909749764cc4a7f9e8 completed Feb. 28, 2026, 1:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69a46c5f07808190aeafebb8e7cd7df9 completed March 1, 2026, 4:42 p.m.
NEDg Description generation batch_69a46cf0592081908803613c91c1ec13 completed March 1, 2026, 4:44 p.m.
NED2 Entity disambiguation (via description) batch_69a46d4df73c8190a0fb6b3dbcb40e50 completed March 1, 2026, 4:46 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.