Triple

T14109816
Position Surface form Disambiguated ID Type / Status
Subject C line (Copenhagen S-train) E339604 entity
Predicate lineDesignation P5539 FINISHED
Object C
C is a Copenhagen S-train commuter rail line that runs through central Copenhagen and connects key suburban areas in the metropolitan network.
E1079519 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: C | Statement: [C line (Copenhagen S-train), lineDesignation, C]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: C
Context triple: [C line (Copenhagen S-train), lineDesignation, C]
  • A. C
    C is a foundational, general-purpose programming language known for its efficiency, low-level memory access, and influence on many later languages such as C++, Java, and Python.
  • B. C
    C is a local service on the New York City Subway that runs along the Eighth Avenue Line in Manhattan and continues through Brooklyn.
  • C. C
    C is a light rail service designation used by the Los Angeles Metro system for one of its primary rail lines.
  • D. C
    C is the New York Stock Exchange ticker symbol for Citigroup Inc., a major global financial services and banking corporation.
  • E. C
    C is one of the three central women in Edward Albee’s play "Three Tall Women," representing a younger stage of the protagonist’s life and perspective.
  • 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: C
Triple: [C line (Copenhagen S-train), lineDesignation, C]
Generated description
C is a Copenhagen S-train commuter rail line that runs through central Copenhagen and connects key suburban areas in the metropolitan network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: C
Target entity description: C is a Copenhagen S-train commuter rail line that runs through central Copenhagen and connects key suburban areas in the metropolitan network.
  • A. C
    C is a light rail service designation used by the Los Angeles Metro system for one of its primary rail lines.
  • B. C
    C is a local service on the New York City Subway that runs along the Eighth Avenue Line in Manhattan and continues through Brooklyn.
  • C. C
    C is the New York Stock Exchange ticker symbol for Citigroup Inc., a major global financial services and banking corporation.
  • D. C
    C is the standard scholarly siglum for Codex Ephraemi Rescriptus, a 5th-century Greek biblical manuscript and palimpsest containing portions of the Old and New Testaments.
  • E. C
    C is a foundational, general-purpose programming language known for its efficiency, low-level memory access, and influence on many later languages such as C++, Java, and Python.
  • 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_69d81c69b5c8819094aa1abf18302908 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de600caf308190ab6d8451ed4e3797 completed April 14, 2026, 3:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcd0b699108190993f1102418ecff1 completed May 7, 2026, 5:49 p.m.
NEDg Description generation batch_69fcd2d99c4c8190baf15d470ead7b1c completed May 7, 2026, 5:58 p.m.
NED2 Entity disambiguation (via description) batch_69fcd3853e848190a210d1c8c08bd6cc completed May 7, 2026, 6:01 p.m.
Created at: April 9, 2026, 10:22 p.m.