Triple

T5716333
Position Surface form Disambiguated ID Type / Status
Subject E233 series EMU E126032 entity
Predicate safetySystem P840 FINISHED
Object ATS-SN
ATS-SN is a Japanese automatic train stop safety system used on conventional railway lines to prevent trains from passing signals at danger.
 E541202 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: ATS-SN | Statement: [E233 series EMU, safetySystem, ATS-SN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ATS-SN
Context triple: [E233 series EMU, safetySystem, ATS-SN]
  • A. ATS
    ATS is the abbreviation for the Auxiliary Territorial Service, the women's branch of the British Army during the Second World War.
  • B. ATS
    ATS is the Antarctic Treaty Secretariat, the international body that supports and coordinates the implementation of the Antarctic Treaty System among its member countries.
  • C. ATS
    ATS is a North American accrediting and membership organization for graduate schools of theology and ministry.
  • D. ATN
    ATN most likely refers to Augmented Transition Network, a type of finite state machine used in computational linguistics and natural language processing for parsing sentences.
  • E. ATAS
    ATAS is the commonly used acronym for the Academy of Television Arts & Sciences, the organization best known for administering the Primetime Emmy Awards.
  • 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: ATS-SN
Triple: [E233 series EMU, safetySystem, ATS-SN]
Generated description
ATS-SN is a Japanese automatic train stop safety system used on conventional railway lines to prevent trains from passing signals at danger.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ATS-SN
Target entity description: ATS-SN is a Japanese automatic train stop safety system used on conventional railway lines to prevent trains from passing signals at danger.
  • A. ATS
    ATS is the abbreviation for the Auxiliary Territorial Service, the women's branch of the British Army during the Second World War.
  • B. ATS
    ATS is the Antarctic Treaty Secretariat, the international body that supports and coordinates the implementation of the Antarctic Treaty System among its member countries.
  • C. ATS
    ATS is a North American accrediting and membership organization for graduate schools of theology and ministry.
  • D. ATN
    ATN most likely refers to Augmented Transition Network, a type of finite state machine used in computational linguistics and natural language processing for parsing sentences.
  • E. ATAS
    ATAS is the commonly used acronym for the Academy of Television Arts & Sciences, the organization best known for administering the Primetime Emmy Awards.
  • 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_69c0082e3d548190950169847b43043b completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c024ba819c8190bb7d775405dda9d6 completed March 22, 2026, 5:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a7af5788190827ff8050eb6416d completed March 22, 2026, 9:09 p.m.
NEDg Description generation batch_69c05c75179c819085bf56340363b48c completed March 22, 2026, 9:17 p.m.
NED2 Entity disambiguation (via description) batch_69c05d2ef9488190ac0111cb6a94b1d0 completed March 22, 2026, 9:20 p.m.
Created at: March 22, 2026, 3:46 p.m.