Triple

T1243624
Position Surface form Disambiguated ID Type / Status
Subject Berlin S-Bahn E26713 entity
Predicate hasLine P35 FINISHED
Object S85
S85 is a suburban rail line of the Berlin S-Bahn network serving routes through the German capital and its surrounding areas.
 E143050 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: S85 | Statement: [Berlin S-Bahn, hasLine, S85]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: S85
Context triple: [Berlin S-Bahn, hasLine, S85]
  • A. S8
    S8 is a line of the Berlin S-Bahn urban rail network serving various districts across the Berlin metropolitan area.
  • B. S5
    S5 is a line of the Berlin S-Bahn rapid transit network serving routes between central Berlin and its eastern suburbs.
  • C. SA5
    SA5 is the 3GPP Service and System Aspects working group responsible for management, orchestration, and operations of mobile communication networks.
  • D. S25
    S25 is a commuter rail line of the Berlin S-Bahn network serving various districts across the Berlin metropolitan area.
  • E. Sauer
    Sauer is a German surname borne by various notable individuals in fields such as science, politics, and the arts.
  • 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: S85
Triple: [Berlin S-Bahn, hasLine, S85]
Generated description
S85 is a suburban rail line of the Berlin S-Bahn network serving routes through the German capital and its surrounding areas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: S85
Target entity description: S85 is a suburban rail line of the Berlin S-Bahn network serving routes through the German capital and its surrounding areas.
  • A. S8
    S8 is a line of the Berlin S-Bahn urban rail network serving various districts across the Berlin metropolitan area.
  • B. S5
    S5 is a line of the Berlin S-Bahn rapid transit network serving routes between central Berlin and its eastern suburbs.
  • C. SA5
    SA5 is the 3GPP Service and System Aspects working group responsible for management, orchestration, and operations of mobile communication networks.
  • D. S25
    S25 is a commuter rail line of the Berlin S-Bahn network serving various districts across the Berlin metropolitan area.
  • E. Sauer
    Sauer is a German surname borne by various notable individuals in fields such as science, politics, and the arts.
  • 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_69a4948689d08190b3a4a3f388c02148 completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4bf636e208190a4d56806db61916c completed March 1, 2026, 10:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac93c186fc8190a353c8f0a90ce273 completed March 7, 2026, 9:08 p.m.
NEDg Description generation batch_69ac94abbd748190851f3d53ec909494 completed March 7, 2026, 9:12 p.m.
NED2 Entity disambiguation (via description) batch_69ac9506ec5481909014834364f4e7f7 completed March 7, 2026, 9:13 p.m.
Created at: March 1, 2026, 7:47 p.m.