Triple

T14554281
Position Surface form Disambiguated ID Type / Status
Subject Military Museum station E341497 entity
Predicate hasLine P35 FINISHED
Object Line 1
Line 1 is a primary metro line of the Beijing Subway, running east–west through the city and serving many of its central districts and key landmarks.
E66114 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 1 | Statement: [Military Museum station, hasLine, Line 1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 1
Context triple: [Military Museum station, hasLine, Line 1]
  • A. Line 1
    Line 1 is a major rapid transit line of the Guangzhou Metro system in Guangzhou, China, serving as one of the city's primary east–west corridors.
  • B. Line 1
    Line 1 is the oldest and one of the busiest lines of the Paris Métro, running primarily east–west through central Paris and serving many major landmarks.
  • C. Line 1
    Line 1 is the numerical designation commonly used for Ottawa’s Confederation Line, the city’s primary light rail transit route.
  • D. Line 1
    Line 1 is the first rapid transit line of the Santo Domingo Metro system, serving as a major north–south corridor through the Dominican Republic’s capital.
  • E. Line 1
    Line 1 is the first and primary rapid transit line of the Sofia Metro system in Bulgaria, connecting key residential districts with the city center and major transport hubs.
  • 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 1
Triple: [Military Museum station, hasLine, Line 1]
Generated description
Line 1 is a primary metro line of the Beijing Subway, running east–west through the city and serving many of its central districts and key landmarks.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Line 1
Target entity description: Line 1 is a primary metro line of the Beijing Subway, running east–west through the city and serving many of its central districts and key landmarks.
  • A. Line 1
    Line 1 is a major Beijing Subway route that runs north–south through the city’s central axis, serving key commercial and historical areas.
  • B. Line 1 chosen
    Line 1 is one of the main east–west rapid transit lines of the Beijing Subway, serving as a core corridor through central Beijing.
  • C. Line 1
    Line 1 is the oldest and one of the busiest lines of the Paris Métro, running primarily east–west through central Paris and serving many major landmarks.
  • D. Line 1
    Line 1 is one of the main lines of the Barcelona Metro rapid transit system, running on a largely east–west axis and serving several key districts of the city.
  • E. Line 1
    Line 1 is a primary rapid transit route of the Shijiazhuang Metro system in Shijiazhuang, China, serving key urban areas along an east–west corridor.
  • F. None of above.

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_69d822db9c8481908213ceb39585f792 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb2f00cec8190a7b6482d18b9a216 completed April 14, 2026, 9:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd8ab9a5ac81908779a3c8701353fa completed May 8, 2026, 7:03 a.m.
NEDg Description generation batch_69fd8be7d8988190807d4db477b91de0 completed May 8, 2026, 7:08 a.m.
NED2 Entity disambiguation (via description) batch_69fd8d4f2e848190a3c4c423c0ffed50 completed May 8, 2026, 7:14 a.m.
Created at: April 10, 2026, 1:23 a.m.