Triple

T20601715
Position Surface form Disambiguated ID Type / Status
Subject Theresienwiese U-Bahn station E506196 entity
Predicate hasStationCode P1289 FINISHED
Object TWS
TWS is the station code for Theresienwiese, a Munich U-Bahn station best known for serving the Oktoberfest grounds.
 E1439582 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: TWS | Statement: [Theresienwiese U-Bahn station, hasStationCode, TWS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TWS
Context triple: [Theresienwiese U-Bahn station, hasStationCode, TWS]
  • A. TWB
    TWB is the IATA airport code for Toowoomba City Aerodrome, a regional airport serving the city of Toowoomba in Queensland, Australia.
  • B. TWB
    TWB is the ICAO airline designator assigned to the South Korean low-cost carrier Tʼway Air.
  • C. TWB
    TWB is the National Rail station code for Tweedbank railway station in the Scottish Borders, Scotland.
  • D. TS
    TS is the vehicle registration code assigned to vehicles registered in Tsageri Municipality in Georgia.
  • E. TS
    TS is the vehicle registration code used on license plates for the Province of Trieste in northeastern Italy.
  • 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: TWS
Triple: [Theresienwiese U-Bahn station, hasStationCode, TWS]
Generated description
TWS is the station code for Theresienwiese, a Munich U-Bahn station best known for serving the Oktoberfest grounds.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TWS
Target entity description: TWS is the station code for Theresienwiese, a Munich U-Bahn station best known for serving the Oktoberfest grounds.
  • A. TWB
    TWB is the IATA airport code for Toowoomba City Aerodrome, a regional airport serving the city of Toowoomba in Queensland, Australia.
  • B. TWB
    TWB is the ICAO airline designator assigned to the South Korean low-cost carrier Tʼway Air.
  • C. TWB
    TWB is the National Rail station code for Tweedbank railway station in the Scottish Borders, Scotland.
  • D. TS
    TS is the vehicle registration code used on license plates for the Province of Trieste in northeastern Italy.
  • E. TS
    TS is the common abbreviation for Windows Terminal Services, Microsoft’s legacy remote desktop and application virtualization technology for Windows servers.
  • 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_69e0b4ba6ae88190af871e1f9522c704 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6aa20f5c881909265ce7d96efc487 completed April 20, 2026, 10:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a08b3f35cb08190a7cdc354534fba1c completed May 16, 2026, 6:14 p.m.
NEDg Description generation batch_6a08b4c5946081909ac59ed47f3ba909 completed May 16, 2026, 6:17 p.m.
NED2 Entity disambiguation (via description) batch_6a08b53450a481909133bd18c34dc78c completed May 16, 2026, 6:19 p.m.
Created at: April 16, 2026, 11:41 a.m.