Triple

T6473374
Position Surface form Disambiguated ID Type / Status
Subject Stadler Rail E146008 entity
Predicate brand P1500 FINISHED
Object WINK
WINK is a type of regional multiple-unit train developed and marketed by Stadler Rail for efficient, flexible passenger service.
 E595581 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: WINK | Statement: [Stadler Rail, brand, WINK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WINK
Context triple: [Stadler Rail, brand, WINK]
  • A. WOB
    WOB is the vehicle registration code used on license plates for cars registered in Wolfsburg, Germany.
  • B. Wicks
    Wicks is a surname most notably associated with former professional basketball player Sidney Wicks.
  • C. WIL
    WIL is the standard abbreviation used for the Wilmington Blue Rocks minor league baseball team.
  • D. WIL
    WIL is the IATA airport code for Wilson Airport, a busy domestic and regional airport serving Nairobi, Kenya.
  • E. WU
    WU is a leading European university in Vienna specializing in economics, business, and social sciences.
  • 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: WINK
Triple: [Stadler Rail, brand, WINK]
Generated description
WINK is a type of regional multiple-unit train developed and marketed by Stadler Rail for efficient, flexible passenger service.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WINK
Target entity description: WINK is a type of regional multiple-unit train developed and marketed by Stadler Rail for efficient, flexible passenger service.
  • A. WOB
    WOB is the vehicle registration code used on license plates for cars registered in Wolfsburg, Germany.
  • B. Wicks
    Wicks is a surname most notably associated with former professional basketball player Sidney Wicks.
  • C. WIL
    WIL is the standard abbreviation used for the Wilmington Blue Rocks minor league baseball team.
  • D. WIL
    WIL is the IATA airport code for Wilson Airport, a busy domestic and regional airport serving Nairobi, Kenya.
  • E. WU
    WU is the stock ticker symbol for Western Union, a global financial services company best known for its money transfer and payment services.
  • 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_69c008fec7408190af7b146dc63d9750 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06a32c0188190bcb3c35fc1d796a6 completed March 22, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c653a2b2508190a3691412f853ed6f completed March 27, 2026, 9:53 a.m.
NEDg Description generation batch_69c6552b90848190961250b1e64595e1 completed March 27, 2026, 10 a.m.
NED2 Entity disambiguation (via description) batch_69c655bce7548190b4c5661a7aaa77e1 completed March 27, 2026, 10:02 a.m.
Created at: March 22, 2026, 4:50 p.m.