Triple

T6546629
Position Surface form Disambiguated ID Type / Status
Subject Russell Square station E151024 entity
Predicate stationCode P1289 FINISHED
Object RUS
RUS is the National Rail station code assigned to Russell Square station in London.
 E604479 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: RUS | Statement: [Russell Square station, stationCode, RUS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: RUS
Context triple: [Russell Square station, stationCode, RUS]
  • A. RUS
    RUS is the acronym for the Rural Utilities Service, a U.S. government agency that provides funding and support for rural infrastructure such as electricity, water, and telecommunications.
  • B. Rus
    Rus was a medieval East Slavic cultural and political realm that laid the foundations for the modern nations of Russia, Ukraine, and Belarus.
  • C. RU
    RU is the common abbreviation for Rutgers University, a major public research institution in New Jersey.
  • D. RU
    RU is the two-letter ISO 3166 country code for the Russian Federation.
  • E. RU
    RU is the historic vehicle registration code that was used for the English county of Rutland.
  • 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: RUS
Triple: [Russell Square station, stationCode, RUS]
Generated description
RUS is the National Rail station code assigned to Russell Square station in London.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: RUS
Target entity description: RUS is the National Rail station code assigned to Russell Square station in London.
  • A. RUS
    RUS is the acronym for the Rural Utilities Service, a U.S. government agency that provides funding and support for rural infrastructure such as electricity, water, and telecommunications.
  • B. Rus
    Rus was a medieval East Slavic cultural and political realm that laid the foundations for the modern nations of Russia, Ukraine, and Belarus.
  • C. RU
    RU is the common abbreviation for Rutgers University, a major public research institution in New Jersey.
  • D. RU
    RU is the two-letter ISO 3166 country code for the Russian Federation.
  • E. RU
    RU is the common abbreviation for Radboud University Nijmegen, a major research university located in Nijmegen, the Netherlands.
  • 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_69c687f3fd60819083bfa583e5bcfa71 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6adf00aa48190a86a9ad4795363d9 completed March 27, 2026, 4:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d54b6d8c819083595375194aee12 completed March 27, 2026, 7:06 p.m.
NEDg Description generation batch_69c6d6acc2208190ac47c60bb896c1cd completed March 27, 2026, 7:12 p.m.
NED2 Entity disambiguation (via description) batch_69c6d83b53e48190881a3e1e8fa8b168 completed March 27, 2026, 7:19 p.m.
Created at: March 27, 2026, 1:50 p.m.