Triple

T1224296
Position Surface form Disambiguated ID Type / Status
Subject Berlin-Wannsee station E26291 entity
Predicate servedByLine P1293 FINISHED
Object S7
S7 is a Berlin S-Bahn rapid transit line that runs across the city, connecting key districts between Potsdam and Ahrensfelde.
E139349 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: S7 | Statement: [Berlin-Wannsee station, servedByLine, S7]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: S7
Context triple: [Berlin-Wannsee station, servedByLine, S7]
  • A. Siemens S70
    The Siemens S70 is a modern low-floor light rail vehicle widely used in North American urban transit systems.
  • B. S-blokka
    S-blokka is a government office building in Oslo, Norway, that forms part of the Norwegian Government Quarter complex.
  • C. Sauer
    Sauer is a German surname borne by various notable individuals in fields such as science, politics, and the arts.
  • D. 7L
    7L is the IATA airline designator assigned to AeroCaribbean, a regional carrier based in Cuba.
  • E. A73
    A73 is a major German autobahn in Bavaria and Thuringia that links cities such as Lichtenfels with the broader national motorway network.
  • 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: S7
Triple: [Berlin-Wannsee station, servedByLine, S7]
Generated description
S7 is a Berlin S-Bahn rapid transit line that runs across the city, connecting key districts between Potsdam and Ahrensfelde.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: S7
Target entity description: S7 is a Berlin S-Bahn rapid transit line that runs across the city, connecting key districts between Potsdam and Ahrensfelde.
  • A. Siemens S70
    The Siemens S70 is a modern low-floor light rail vehicle widely used in North American urban transit systems.
  • B. S-blokka
    S-blokka is a government office building in Oslo, Norway, that forms part of the Norwegian Government Quarter complex.
  • C. Sauer
    Sauer is a German surname borne by various notable individuals in fields such as science, politics, and the arts.
  • D. 7L
    7L is the IATA airline designator assigned to AeroCaribbean, a regional carrier based in Cuba.
  • E. A73
    A73 is a major German autobahn in Bavaria and Thuringia that links cities such as Lichtenfels with the broader national motorway network.
  • 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_69a49484688c8190a1bf285eb396a8b6 completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be233fd88190996faf4105c0b8d7 completed March 1, 2026, 10:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac832704c08190a1a73ebd90fa91b8 completed March 7, 2026, 7:57 p.m.
NEDg Description generation batch_69ac83add3608190be198ba153721d5c completed March 7, 2026, 7:59 p.m.
NED2 Entity disambiguation (via description) batch_69ac846e724081909696c8c44f2f9500 completed March 7, 2026, 8:02 p.m.
Created at: March 1, 2026, 7:47 p.m.