Triple

T7323579
Position Surface form Disambiguated ID Type / Status
Subject Lutherstadt Wittenberg station E168811 entity
Predicate hasStationCode P1289 FINISHED
Object WL
WL is the station code for Lutherstadt Wittenberg railway station in Germany.
 E657648 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: WL | Statement: [Lutherstadt Wittenberg station, hasStationCode, WL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WL
Context triple: [Lutherstadt Wittenberg station, hasStationCode, WL]
  • A. WN
    WN is the IATA airline designator used to identify Southwest Airlines in flight schedules, ticketing, and aviation operations.
  • B. WN
    WN is the vehicle registration code used on license plates for the Waiblingen district in the German state of Baden-Württemberg.
  • C. WM
    WM was the reporting mark for the Western Maryland Railway, a regional U.S. railroad that later became part of the Chessie System.
  • D. WC
    WC is an American West Coast rapper known for his distinctive gravelly voice, solo work, and as a member of the hip hop supergroup Westside Connection.
  • E. WC
    WC is the standard abbreviation for Western Command, a regional military command formation.
  • 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: WL
Triple: [Lutherstadt Wittenberg station, hasStationCode, WL]
Generated description
WL is the station code for Lutherstadt Wittenberg railway station in Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WL
Target entity description: WL is the station code for Lutherstadt Wittenberg railway station in Germany.
  • A. WN
    WN is the vehicle registration code used on license plates for the Waiblingen district in the German state of Baden-Württemberg.
  • B. WN
    WN is the IATA airline designator used to identify Southwest Airlines in flight schedules, ticketing, and aviation operations.
  • C. WM
    WM was the reporting mark for the Western Maryland Railway, a regional U.S. railroad that later became part of the Chessie System.
  • D. WC
    WC is an American West Coast rapper known for his distinctive gravelly voice, solo work, and as a member of the hip hop supergroup Westside Connection.
  • E. WC
    WC is the standard abbreviation for Western Command, a regional military command formation.
  • 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_69c68a54cacc81908e3b773441f19566 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f046b93c8190a80dd48ee409ec5d completed March 27, 2026, 9:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7ef0a1200819089fe3e18493d8bee completed March 28, 2026, 3:08 p.m.
NEDg Description generation batch_69c7ef7f7b7c8190b3361cc01b2eefc0 completed March 28, 2026, 3:10 p.m.
NED2 Entity disambiguation (via description) batch_69c7f380dbe48190933e1eeff109185d completed March 28, 2026, 3:28 p.m.
Created at: March 27, 2026, 3:03 p.m.