Triple

T1140280
Position Surface form Disambiguated ID Type / Status
Subject Office of Rail and Road E23433 entity
Predicate shortName P43 FINISHED
Object ORR
ORR is the independent regulator and competition authority for Britain’s railways and the monitor of National Highways in England.
 E129609 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: ORR | Statement: [Office of Rail and Road, shortName, ORR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ORR
Context triple: [Office of Rail and Road, shortName, ORR]
  • A. OAR
    OAR is the commonly used abbreviation for the Oregon Administrative Rules, which comprise the codified regulations issued by Oregon’s state agencies.
  • B. OAR
    OAR is the commonly used acronym for the U.S. Environmental Protection Agency’s Office of Air and Radiation, which oversees national efforts to protect and improve air quality and control radiation exposure.
  • C. OR
    OR is the official two-letter United States Postal Service abbreviation for the state of Oregon.
  • D. ORC
    ORC (Optimized Row Columnar) is a highly efficient, columnar storage file format commonly used in big data systems to enable fast analytics and compression.
  • E. OLR
    OLR is the common abbreviation for OL Reign, a professional women’s soccer club based in the United States that competes in the National Women’s Soccer League.
  • 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: ORR
Triple: [Office of Rail and Road, shortName, ORR]
Generated description
ORR is the independent regulator and competition authority for Britain’s railways and the monitor of National Highways in England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ORR
Target entity description: ORR is the independent regulator and competition authority for Britain’s railways and the monitor of National Highways in England.
  • A. OAR
    OAR is the commonly used abbreviation for the Oregon Administrative Rules, which comprise the codified regulations issued by Oregon’s state agencies.
  • B. OAR
    OAR is the commonly used acronym for the U.S. Environmental Protection Agency’s Office of Air and Radiation, which oversees national efforts to protect and improve air quality and control radiation exposure.
  • C. OR
    OR is the official two-letter United States Postal Service abbreviation for the state of Oregon.
  • D. ORC
    ORC (Optimized Row Columnar) is a highly efficient, columnar storage file format commonly used in big data systems to enable fast analytics and compression.
  • E. OLR
    OLR is the common abbreviation for OL Reign, a professional women’s soccer club based in the United States that competes in the National Women’s Soccer League.
  • 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_69a493ef399c8190b04b9146d2314f59 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4bc290ae08190afbf7e7ea2100d9e completed March 1, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac59b020d48190bc6ecbdb720c6779 completed March 7, 2026, 5 p.m.
NEDg Description generation batch_69ac5a7599048190a46b0d560270ffa4 completed March 7, 2026, 5:03 p.m.
NED2 Entity disambiguation (via description) batch_69ac5af24a948190a37c832508149a48 completed March 7, 2026, 5:05 p.m.
Created at: March 1, 2026, 7:44 p.m.