Triple

T4150843
Position Surface form Disambiguated ID Type / Status
Subject Brickell Metrorail station E89898 entity
Predicate lineColor P60 FINISHED
Object Orange
Orange is one of the color-coded lines of Miami’s Metrorail system, serving as a distinct route that includes Brickell station among its stops.
 E416866 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: Orange | Statement: [Brickell Metrorail station, lineColor, Orange]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Orange
Context triple: [Brickell Metrorail station, lineColor, Orange]
  • A. Orange
    Orange is a major French multinational telecommunications company providing mobile, internet, and other digital services across numerous countries.
  • B. Orange
    Orange is the nickname and primary identity of Syracuse University's athletic teams, especially its prominent men's basketball program.
  • C. Orange
    Orange was the original name of the town now known as Hillsborough in North Carolina, reflecting its early colonial-era identity.
  • D. Orange
    Orange is a historic town in southeastern France best known for giving its name and origin to the Dutch royal House of Orange-Nassau.
  • E. Orange
    Orange is a small suburban village in Cuyahoga County, Ohio, known for its residential character and proximity to the Cleveland metropolitan area.
  • 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: Orange
Triple: [Brickell Metrorail station, lineColor, Orange]
Generated description
Orange is one of the color-coded lines of Miami’s Metrorail system, serving as a distinct route that includes Brickell station among its stops.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Orange
Target entity description: Orange is one of the color-coded lines of Miami’s Metrorail system, serving as a distinct route that includes Brickell station among its stops.
  • A. Orange
    Orange is a citrus-flavored sports drink variety known for its bright, tangy taste and association with energy and hydration.
  • B. Orange
    Orange is a small suburban village in Cuyahoga County, Ohio, known for its residential character and proximity to the Cleveland metropolitan area.
  • C. Orange
    Orange is a major French multinational telecommunications company providing mobile, internet, and other digital services across numerous countries.
  • D. Orange
    Orange is the nickname and primary identity of Syracuse University's athletic teams, especially its prominent men's basketball program.
  • E. Orange
    Orange is a historic town in southeastern France best known for giving its name and origin to the Dutch royal House of Orange-Nassau.
  • 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_69aed95a59a881909b26e70b42c6811a completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af0274f440819087dd58a9ce45cce5 completed March 9, 2026, 5:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69b57f3707a8819082bafd0d11b7359f completed March 14, 2026, 3:31 p.m.
NEDg Description generation batch_69b58059d9808190873c920886c31131 completed March 14, 2026, 3:35 p.m.
NED2 Entity disambiguation (via description) batch_69b580d448708190a722c25726a40562 completed March 14, 2026, 3:37 p.m.
Created at: March 9, 2026, 3:43 p.m.