Triple

T11461481
Position Surface form Disambiguated ID Type / Status
Subject Noisy-le-Grand E271669 entity
Predicate roadAccess P385 FINISHED
Object RN370
RN370 is a French national road that serves as a key regional connector in the eastern suburbs of Paris, including access to the commune of Noisy-le-Grand.
 E927816 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: RN370 | Statement: [Noisy-le-Grand, roadAccess, RN370]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: RN370
Context triple: [Noisy-le-Grand, roadAccess, RN370]
  • A. RN12
    RN12 is a major national road in France that serves as an important route connecting several towns and regions in the western part of the country.
  • B. R37
    R37 is a regional road in South Africa that serves as a key route connecting the town of Lydenburg with other parts of the Mpumalanga and Limpopo provinces.
  • C. R37
    R37 is a regional commuter rail line in Catalonia that forms part of the Rodalies de Catalunya network.
  • D. RN6
    RN6 is a former designation for a national road that has since been renumbered or reclassified within the road network.
  • E. RN104
    RN104, also called the Francilienne, is a major ring road in the Île-de-France region that serves as an outer bypass around Paris.
  • 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: RN370
Triple: [Noisy-le-Grand, roadAccess, RN370]
Generated description
RN370 is a French national road that serves as a key regional connector in the eastern suburbs of Paris, including access to the commune of Noisy-le-Grand.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: RN370
Target entity description: RN370 is a French national road that serves as a key regional connector in the eastern suburbs of Paris, including access to the commune of Noisy-le-Grand.
  • A. RN12
    RN12 is a major national road in France that serves as an important route connecting several towns and regions in the western part of the country.
  • B. R37
    R37 is a regional road in South Africa that serves as a key route connecting the town of Lydenburg with other parts of the Mpumalanga and Limpopo provinces.
  • C. R37
    R37 is a regional commuter rail line in Catalonia that forms part of the Rodalies de Catalunya network.
  • D. RN6
    RN6 is a former designation for a national road that has since been renumbered or reclassified within the road network.
  • E. RN104
    RN104, also called the Francilienne, is a major ring road in the Île-de-France region that serves as an outer bypass around Paris.
  • 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_69d6aae0c8d881908a5a360c0be3242e completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d822f384f08190b1150ed1389dd31a completed April 9, 2026, 10:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5e91f1bb881909a9c36d837e4059b completed April 20, 2026, 8:51 a.m.
NEDg Description generation batch_69e5f1593c2c8190885f80ad5eeba3ec completed April 20, 2026, 9:26 a.m.
NED2 Entity disambiguation (via description) batch_69e5f87bbd988190ac388a3c34b2e95a completed April 20, 2026, 9:57 a.m.
Created at: April 8, 2026, 9:35 p.m.