Triple

T9590218
Position Surface form Disambiguated ID Type / Status
Subject Korea Exchange E231396 entity
Predicate index P1393 FINISHED
Object KRX 300
KRX 300 is a South Korean stock market index that tracks the performance of 300 representative companies listed on the Korea Exchange.
E809622 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: KRX 300 | Statement: [Korea Exchange, index, KRX 300]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KRX 300
Context triple: [Korea Exchange, index, KRX 300]
  • A. KRX 100
    KRX 100 is a major South Korean stock market index that tracks the performance of 100 representative companies listed on the Korea Exchange.
  • B. KR-48
    KR-48 is the ISO 3166-2 subdivision code assigned to South Korea’s South Gyeongsang Province, which includes the city of Miryang.
  • C. KJ-500
    The KJ-500 is a modern Chinese airborne early warning and control (AEW&C) aircraft featuring a fixed dorsal radar dome and advanced phased-array radar systems for long-range airspace surveillance and battle management.
  • D. XKRX
    XKRX is the Market Identifier Code (MIC) for the Korea Exchange, South Korea’s main securities and derivatives marketplace.
  • E. Kinkisharyo P3010
    The Kinkisharyo P3010 is a modern light rail vehicle used by the Los Angeles Metro system, known for its low-floor design and operation across several of the city's rail lines.
  • 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: KRX 300
Triple: [Korea Exchange, index, KRX 300]
Generated description
KRX 300 is a South Korean stock market index that tracks the performance of 300 representative companies listed on the Korea Exchange.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: KRX 300
Target entity description: KRX 300 is a South Korean stock market index that tracks the performance of 300 representative companies listed on the Korea Exchange.
  • A. KRX 100
    KRX 100 is a major South Korean stock market index that tracks the performance of 100 representative companies listed on the Korea Exchange.
  • B. KR-48
    KR-48 is the ISO 3166-2 subdivision code assigned to South Korea’s South Gyeongsang Province, which includes the city of Miryang.
  • C. KJ-500
    The KJ-500 is a modern Chinese airborne early warning and control (AEW&C) aircraft featuring a fixed dorsal radar dome and advanced phased-array radar systems for long-range airspace surveillance and battle management.
  • D. XKRX
    XKRX is the Market Identifier Code (MIC) for the Korea Exchange, South Korea’s main securities and derivatives marketplace.
  • E. Kinkisharyo P3010
    The Kinkisharyo P3010 is a modern light rail vehicle used by the Los Angeles Metro system, known for its low-floor design and operation across several of the city's rail lines.
  • 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_69ca8482884481908eccdfdf64d6fbf7 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd99f32e688190bb13bccfa5031f16 completed April 1, 2026, 10:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1791e330881908a6ad31a5bdbccec completed April 4, 2026, 8:48 p.m.
NEDg Description generation batch_69d179e99d6481909d31145b6e627a29 completed April 4, 2026, 8:51 p.m.
NED2 Entity disambiguation (via description) batch_69d17a3aebfc8190acbe62ac900dd9e7 completed April 4, 2026, 8:53 p.m.
Created at: March 30, 2026, 8:06 p.m.