Triple

T18383265
Position Surface form Disambiguated ID Type / Status
Subject Beitucheng station E446509 entity
Predicate hasExit P6140 FINISHED
Object Exit F
Exit F is one of the designated passenger exits at Beitucheng Station in the Beijing Subway system.
 E1321641 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: Exit F | Statement: [Beitucheng station, hasExit, Exit F]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Exit F
Context triple: [Beitucheng station, hasExit, Exit F]
  • A. F
    F is a tram line in the Strasbourg tramway network in France, serving various districts of the city and its suburbs.
  • B. F
    F is the New York Stock Exchange ticker symbol for Ford Motor Company, the American multinational automaker known for mass-producing automobiles and pioneering assembly line manufacturing.
  • C. F
    The F is a New York City Subway service that runs along the IND Sixth Avenue Line in Manhattan and Queens Boulevard Line in Queens, connecting Brooklyn, Manhattan, and Queens.
  • D. EF
    EF is the commonly used abbreviation for the Eclipse Foundation, a nonprofit organization that oversees open-source software projects and the Eclipse IDE ecosystem.
  • E. EF
    EF is the vehicle registration code used on license plates for the German city of Erfurt.
  • 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: Exit F
Triple: [Beitucheng station, hasExit, Exit F]
Generated description
Exit F is one of the designated passenger exits at Beitucheng Station in the Beijing Subway system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Exit F
Target entity description: Exit F is one of the designated passenger exits at Beitucheng Station in the Beijing Subway system.
  • A. F
    F is the New York Stock Exchange ticker symbol for Ford Motor Company, the American multinational automaker known for mass-producing automobiles and pioneering assembly line manufacturing.
  • B. F
    F is a tram line in the Strasbourg tramway network in France, serving various districts of the city and its suburbs.
  • C. F
    The F is a New York City Subway service that runs along the IND Sixth Avenue Line in Manhattan and Queens Boulevard Line in Queens, connecting Brooklyn, Manhattan, and Queens.
  • D. EF
    EF is the commonly used abbreviation for the Eclipse Foundation, a nonprofit organization that oversees open-source software projects and the Eclipse IDE ecosystem.
  • E. EF
    EF is the vehicle registration code used on license plates for the German city of Erfurt.
  • 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_69d8b9f370b88190b1e5081c2c238e7f completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e5179c931c8190b1c7c8284f42f7b7 completed April 19, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a03d782cb54819091b847cdeb98ed5c completed May 13, 2026, 1:44 a.m.
NEDg Description generation batch_6a03d8adc00c81908ca0a4825a2bcea1 completed May 13, 2026, 1:49 a.m.
NED2 Entity disambiguation (via description) batch_6a03da59c1b081908d9488233c611586 completed May 13, 2026, 1:56 a.m.
Created at: April 10, 2026, 10:45 a.m.