Triple

T11893953
Position Surface form Disambiguated ID Type / Status
Subject Line 5–Lilac E282988 entity
Predicate connectsWith P37 FINISHED
Object Line 9–Emerald
Line 9–Emerald is a New York City Subway service running along the Lexington Avenue Line in Manhattan and into Brooklyn, typically designated by the dark green color on subway maps.
 E952229 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: Line 9–Emerald | Statement: [Line 5–Lilac, connectsWith, Line 9–Emerald]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 9–Emerald
Context triple: [Line 5–Lilac, connectsWith, Line 9–Emerald]
  • A. Line 9
    Line 9 is a line of the Mexico City Metro system that serves as one of its key rapid transit routes across the city.
  • B. Line 9
    Line 9 is a rapid transit line of the Chongqing Metro system in Chongqing, China, serving as part of the city's expanding urban rail network.
  • C. Line 9
    Line 9 is a rapid transit line of the Beijing Subway system that serves as part of the city's urban rail network.
  • D. Line 9
    Line 9 is a rapid transit route within the STC Metro system, serving as one of its numbered urban rail lines.
  • E. Line 9
    Line 9 is a rapid transit line of the Guangzhou Metro system serving parts of Guangzhou, China.
  • 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: Line 9–Emerald
Triple: [Line 5–Lilac, connectsWith, Line 9–Emerald]
Generated description
Line 9–Emerald is a New York City Subway service running along the Lexington Avenue Line in Manhattan and into Brooklyn, typically designated by the dark green color on subway maps.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line 9–Emerald
Target entity description: Line 9–Emerald is a New York City Subway service running along the Lexington Avenue Line in Manhattan and into Brooklyn, typically designated by the dark green color on subway maps.
  • A. Line 9
    Line 9 is a line of the Mexico City Metro system that serves as one of its key rapid transit routes across the city.
  • B. Line 9
    Line 9 is a rapid transit line of the Chongqing Metro system in Chongqing, China, serving as part of the city's expanding urban rail network.
  • C. Line 9
    Line 9 is a rapid transit line of the Beijing Subway system that serves as part of the city's urban rail network.
  • D. Line 9
    Line 9 is a rapid transit route within the STC Metro system, serving as one of its numbered urban rail lines.
  • E. Line 9
    Line 9 is a rapid transit line of the Guangzhou Metro system serving parts of Guangzhou, China.
  • 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_69d6ab2a90b08190a4e818821cc93e6d completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8dd1172988190a2c13d37220f2f93 completed April 10, 2026, 11:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69f4180569ac81909137d56374e800c0 completed May 1, 2026, 3:03 a.m.
NEDg Description generation batch_69f41f1abaa481908b8a6873a07af848 completed May 1, 2026, 3:33 a.m.
NED2 Entity disambiguation (via description) batch_69f42283c4cc81909793834ef65d2514 completed May 1, 2026, 3:48 a.m.
Created at: April 8, 2026, 9:44 p.m.