Triple

T1514749
Position Surface form Disambiguated ID Type / Status
Subject Amsterdam Metro network E32093 entity
Predicate hasLineColor P9560 FINISHED
Object Line 53 – red
Line 53 – red is a route on the Amsterdam Metro system, distinguished by its red color on transit maps and signage.
 E172718 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 53 – red | Statement: [Amsterdam Metro network, hasLineColor, Line 53 – red]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 53 – red
Context triple: [Amsterdam Metro network, hasLineColor, Line 53 – red]
  • A. Line 5
    Line 5 is one of the main lines of the Santiago Metro in Chile, running across several key districts and serving as a major east–west transit corridor in the city.
  • B. Line 5
    Line 5 is a major north–south route of the Beijing Subway known for connecting key residential and commercial areas through the city center.
  • C. Line 5
    Line 5 is one of the lines of the Mexico City Metro system, serving multiple stations across the city as part of its rapid transit network.
  • D. Line 5
    Line 5 is a route of Mexico City’s Metrobús bus rapid transit system that serves key corridors with dedicated lanes and high-capacity articulated buses.
  • E. Line 3
    Line 3 is a route of Mexico City’s Metrobús bus rapid transit system that serves key corridors with dedicated lanes and high-capacity articulated buses.
  • 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 53 – red
Triple: [Amsterdam Metro network, hasLineColor, Line 53 – red]
Generated description
Line 53 – red is a route on the Amsterdam Metro system, distinguished by its red color on transit maps and signage.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line 53 – red
Target entity description: Line 53 – red is a route on the Amsterdam Metro system, distinguished by its red color on transit maps and signage.
  • A. Line 5
    Line 5 is one of the main lines of the Santiago Metro in Chile, running across several key districts and serving as a major east–west transit corridor in the city.
  • B. Line 5
    Line 5 is one of the lines of the Mexico City Metro system, serving multiple stations across the city as part of its rapid transit network.
  • C. Line 5
    Line 5 is a major north–south route of the Beijing Subway known for connecting key residential and commercial areas through the city center.
  • D. Line 5
    Line 5 is a route of Mexico City’s Metrobús bus rapid transit system that serves key corridors with dedicated lanes and high-capacity articulated buses.
  • E. Line 3
    Line 3 is a route of Mexico City’s Metrobús bus rapid transit system that serves key corridors with dedicated lanes and high-capacity articulated buses.
  • 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_69a885e8caf88190a5fbb6159ce87786 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a907da75388190bfbdbedbd46adbdc completed March 5, 2026, 4:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad23429f1c81909f435030de687675 completed March 8, 2026, 7:20 a.m.
NEDg Description generation batch_69ad24acd82481908b052cecb555b213 completed March 8, 2026, 7:26 a.m.
NED2 Entity disambiguation (via description) batch_69ad254d930c81908932aa76640121ba completed March 8, 2026, 7:29 a.m.
Created at: March 4, 2026, 7:26 p.m.