Triple

T2254041
Position Surface form Disambiguated ID Type / Status
Subject M73 motorway E49678 entity
Predicate hasRouteNumber P1864 FINISHED
Object M73
M73 is a short motorway in central Scotland that links the M74 and M80 motorways, serving as part of the main route around the east of Glasgow.
 E247217 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: M73 | Statement: [M73 motorway, hasRouteNumber, M73]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: M73
Context triple: [M73 motorway, hasRouteNumber, M73]
  • A. M-72
    M-72 is a state highway in northern Michigan that serves as a key east–west route connecting Traverse City with several inland communities and recreational areas.
  • B. M90
    M90 is a major motorway in Scotland that connects Perth to the Forth Road Bridge, forming a key part of the route between the Scottish Highlands and Edinburgh.
  • C. M32
    M32 is a compact dwarf elliptical galaxy that orbits the Andromeda Galaxy within the Local Group.
  • D. MF 77
    MF 77 is a steel-wheeled electric multiple unit train used on several lines of the Paris Métro, introduced in the late 1970s to modernize the network’s rolling stock.
  • E. A73
    A73 is a major German autobahn in Bavaria and Thuringia that links cities such as Lichtenfels with the broader national motorway network.
  • 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: M73
Triple: [M73 motorway, hasRouteNumber, M73]
Generated description
M73 is a short motorway in central Scotland that links the M74 and M80 motorways, serving as part of the main route around the east of Glasgow.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: M73
Target entity description: M73 is a short motorway in central Scotland that links the M74 and M80 motorways, serving as part of the main route around the east of Glasgow.
  • A. M-72
    M-72 is a state highway in northern Michigan that serves as a key east–west route connecting Traverse City with several inland communities and recreational areas.
  • B. M90
    M90 is a major motorway in Scotland that connects Perth to the Forth Road Bridge, forming a key part of the route between the Scottish Highlands and Edinburgh.
  • C. M32
    M32 is a compact dwarf elliptical galaxy that orbits the Andromeda Galaxy within the Local Group.
  • D. MF 77
    MF 77 is a steel-wheeled electric multiple unit train used on several lines of the Paris Métro, introduced in the late 1970s to modernize the network’s rolling stock.
  • E. A73
    A73 is a major German autobahn in Bavaria and Thuringia that links cities such as Lichtenfels with the broader national motorway network.
  • 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_69a88aaa9250819095e127d0d77e8a32 completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc12029548190af9f2cdd7a4de2d6 completed March 7, 2026, 6:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6b1dd6fc8190bd762fb3a17258b0 completed March 9, 2026, 6:39 a.m.
NEDg Description generation batch_69ae6bbdef14819084b96389435ca080 completed March 9, 2026, 6:42 a.m.
NED2 Entity disambiguation (via description) batch_69ae6c2cfac48190b0425088e79cd122 completed March 9, 2026, 6:43 a.m.
Created at: March 4, 2026, 7:47 p.m.