Triple

T2781274
Position Surface form Disambiguated ID Type / Status
Subject Frankfurt Hauptwache station E61699 entity
Predicate servedBy P82 FINISHED
Object S3 line
The S3 line is a route of the Rhine-Main S-Bahn network serving the Frankfurt metropolitan area in Germany.
 E297620 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: [Frankfurt Hauptwache station, servedBy, S3 line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: S3 line
Context triple: [Frankfurt Hauptwache station, servedBy, S3 line]
  • A. Line 3
    Line 3 is one of the main lines of the Mexico City Metro system, running in a generally north–south direction and serving several key residential and commercial areas.
  • B. Line 3
    Line 3 is a major line of the Moscow Metro system, known for serving central Moscow and connecting key residential and commercial districts.
  • C. Line 3
    Line 3 is a major trolleybus route within Geneva’s public transport system, connecting key districts of the city.
  • D. 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.
  • 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: S3 line
Triple: [Frankfurt Hauptwache station, servedBy, S3 line]
Generated description
The S3 line is a route of the Rhine-Main S-Bahn network serving the Frankfurt metropolitan area in Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: S3 line
Target entity description: The S3 line is a route of the Rhine-Main S-Bahn network serving the Frankfurt metropolitan area in Germany.
  • A. Line 3
    Line 3 is one of the main lines of the Mexico City Metro system, running in a generally north–south direction and serving several key residential and commercial areas.
  • B. Line 3
    Line 3 is a major trolleybus route within Geneva’s public transport system, connecting key districts of the city.
  • C. 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.
  • D. Line 3
    Line 3 is a major line of the Moscow Metro system, known for serving central Moscow and connecting key residential and commercial districts.
  • 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_69ab4b7e43c48190997b8fc8fb1663ab completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdd997ebc8190bff88fe549827615 completed March 7, 2026, 8:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc05f4e7881908bf5b6f7df331041 completed March 10, 2026, 6:55 a.m.
NEDg Description generation batch_69afc1d3bec0819087bb787b7f570ddc completed March 10, 2026, 7:01 a.m.
NED2 Entity disambiguation (via description) batch_69afc229caf88190a26959c27e6a1a9e completed March 10, 2026, 7:03 a.m.
Created at: March 6, 2026, 9:57 p.m.