Triple

T12724974
Position Surface form Disambiguated ID Type / Status
Subject Arnos Grove E304080 entity
Predicate stationCode P1289 FINISHED
Object ARG
ARG is the National Rail station code assigned to Arnos Grove station in London.
E1000993 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: ARG | Statement: [Arnos Grove, stationCode, ARG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ARG
Context triple: [Arnos Grove, stationCode, ARG]
  • A. ARG
    ARG is the three-letter ISO 3166-1 alpha-3 country code that uniquely identifies Argentina in international standards and data systems.
  • B. AG
    AG is an Indonesian vehicle registration code used for motor vehicles registered in certain regions of East Java, including Trenggalek.
  • C. AG
    AG is the standard abbreviation for the United States Attorney General, the chief law enforcement officer and head of the U.S. Department of Justice.
  • D. AG
    AG is the Swiss vehicle registration code for the canton of Aargau.
  • E. AG
    AG is the vehicle registration code used on license plates for cars registered in Argeș County, Romania.
  • 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: ARG
Triple: [Arnos Grove, stationCode, ARG]
Generated description
ARG is the National Rail station code assigned to Arnos Grove station in London.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: ARG
Target entity description: ARG is the National Rail station code assigned to Arnos Grove station in London.
  • A. ARG
    ARG is the three-letter ISO 3166-1 alpha-3 country code that uniquely identifies Argentina in international standards and data systems.
  • B. AG
    AG is the common abbreviation for the Christian missions organization To the Nations.
  • C. AG
    AG is an Indonesian vehicle registration code used for motor vehicles registered in certain regions of East Java, including Trenggalek.
  • D. AG
    AG is the standard abbreviation for the United States Attorney General, the chief law enforcement officer and head of the U.S. Department of Justice.
  • E. AG
    AG is the vehicle registration code used on license plates for cars registered in Argeș County, Romania.
  • 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_69d7bdf084148190ab9d513dc0735af4 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96415ebe48190ae935bc3a9b00f65 completed April 10, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67c85c6b88190bbdd94a43915a7a4 completed May 2, 2026, 10:36 p.m.
NEDg Description generation batch_69f67d888d7c8190b9aaeb877984a403 completed May 2, 2026, 10:41 p.m.
NED2 Entity disambiguation (via description) batch_69f67e0f48e4819085905564f5540f37 completed May 2, 2026, 10:43 p.m.
Created at: April 9, 2026, 5:25 p.m.