Triple

T7384719
Position Surface form Disambiguated ID Type / Status
Subject Nanjing Metro E170351 entity
Predicate hasLine P35 FINISHED
Object S3 Line
The S3 Line is a rapid transit route within the Nanjing Metro system in Nanjing, China.
E660754 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: S3 Line | Statement: [Nanjing Metro, hasLine, S3 Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: S3 Line
Context triple: [Nanjing Metro, hasLine, S3 Line]
  • A. S3 line
    The S3 line is a route of the Berlin S-Bahn urban rail network that connects various districts across the city and serves stations such as Berlin Grunewald.
  • B. S3 line
    The S3 line is a commuter rail service within the Zürich S-Bahn network that connects Zürich with its surrounding suburbs and regional destinations.
  • C. S3 line
    The S3 line is a route of the Rhine-Main S-Bahn network serving the Frankfurt metropolitan area in Germany.
  • D. 3 Line
    The 3 Line is a New York City Subway service that runs on the IRT Eastern Parkway and Lenox Avenue lines, connecting Brooklyn with Manhattan and the Bronx.
  • E. Line 3
    Line 3 is a major rapid transit route of the STC Metro system, serving key districts along its corridor.
  • 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: S3 Line
Triple: [Nanjing Metro, hasLine, S3 Line]
Generated description
The S3 Line is a rapid transit route within the Nanjing Metro system in Nanjing, China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: S3 Line
Target entity description: The S3 Line is a rapid transit route within the Nanjing Metro system in Nanjing, China.
  • A. S3 line
    The S3 line is a commuter rail service within the Zürich S-Bahn network that connects Zürich with its surrounding suburbs and regional destinations.
  • B. S3 line
    The S3 line is a route of the Berlin S-Bahn urban rail network that connects various districts across the city and serves stations such as Berlin Grunewald.
  • C. S3 line
    The S3 line is a route of the Rhine-Main S-Bahn network serving the Frankfurt metropolitan area in Germany.
  • D. 3 Line
    The 3 Line is a New York City Subway service that runs on the IRT Eastern Parkway and Lenox Avenue lines, connecting Brooklyn with Manhattan and the Bronx.
  • E. Line 3
    Line 3 is one of the main lines of the Barcelona Metro system, running through central parts of the city and connecting several key stations and neighborhoods.
  • 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_69c68a5d0ed08190b6d361e68f813330 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f1efe1308190b96eefbff56140be completed March 27, 2026, 9:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69c802e23714819094a1b31c82a27fee completed March 28, 2026, 4:33 p.m.
NEDg Description generation batch_69c8038127408190947cb7002ccc0dec completed March 28, 2026, 4:36 p.m.
NED2 Entity disambiguation (via description) batch_69c8040a40088190b37192429678fd3e completed March 28, 2026, 4:38 p.m.
Created at: March 27, 2026, 3:08 p.m.