Triple

T5453388
Position Surface form Disambiguated ID Type / Status
Subject British Rail Class 180 E122420 entity
Predicate hasSafetySystem P2368 FINISHED
Object OTMR
OTMR is an on-train data recording system used on British rail vehicles to log operational and safety-related information for monitoring and incident investigation.
 E520728 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: OTMR | Statement: [British Rail Class 180, hasSafetySystem, OTMR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: OTMR
Context triple: [British Rail Class 180, hasSafetySystem, OTMR]
  • A. OMTR
    OMTR was the NASDAQ stock ticker symbol for Omniture, a web analytics and online marketing optimization company later acquired by Adobe.
  • B. MTM
    MTM is the Mercury Transfer Module of the BepiColombo mission, responsible for propelling and guiding the spacecraft on its journey to Mercury.
  • C. OTT
    OTT is the standard three-letter abbreviation used for the National Hockey League team, the Ottawa Senators.
  • D. OM
    OM is an American experimental rock band known for its hypnotic, drone-influenced sound and spiritually themed compositions.
  • E. OM
    OM is the commonly used abbreviation for Olympique de Marseille, a major French professional football club based in Marseille.
  • 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: OTMR
Triple: [British Rail Class 180, hasSafetySystem, OTMR]
Generated description
OTMR is an on-train data recording system used on British rail vehicles to log operational and safety-related information for monitoring and incident investigation.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: OTMR
Target entity description: OTMR is an on-train data recording system used on British rail vehicles to log operational and safety-related information for monitoring and incident investigation.
  • A. OMTR
    OMTR was the NASDAQ stock ticker symbol for Omniture, a web analytics and online marketing optimization company later acquired by Adobe.
  • B. MTM
    MTM is the Mercury Transfer Module of the BepiColombo mission, responsible for propelling and guiding the spacecraft on its journey to Mercury.
  • C. OTT
    OTT is the standard three-letter abbreviation used for the National Hockey League team, the Ottawa Senators.
  • D. OM
    OM is an American experimental rock band known for its hypnotic, drone-influenced sound and spiritually themed compositions.
  • E. OM
    OM is the commonly used abbreviation for Olympique de Marseille, a major French professional football club based in Marseille.
  • 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_69bd46424248819085282ddf50a565f3 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd91e170f48190b47419b5e2ff71a4 completed March 20, 2026, 6:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf4140248081908c7f42b91579a837 completed March 22, 2026, 1:09 a.m.
NEDg Description generation batch_69bf41dd96448190973b7241df5dbb24 completed March 22, 2026, 1:11 a.m.
NED2 Entity disambiguation (via description) batch_69bf42b97d40819087a98c1cc58bb964 completed March 22, 2026, 1:15 a.m.
Created at: March 20, 2026, 2:08 p.m.