Triple

T15864495
Position Surface form Disambiguated ID Type / Status
Subject Zwickau district E384673 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object WDA
WDA is a German vehicle registration code assigned to the Zwickau district in the state of Saxony.
 E1182051 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: WDA | Statement: [Zwickau district, vehicleRegistrationCode, WDA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WDA
Context triple: [Zwickau district, vehicleRegistrationCode, WDA]
  • A. Wda
    Wda is a river in northern Poland that flows through the Pomeranian region and is known for its scenic, forested course and popularity for kayaking and canoeing.
  • B. WDS
    WDS is the IATA airport code for Shiyan Wudangshan Airport, a regional airport serving the Shiyan and Wudangshan area in Hubei, China.
  • C. WADW
    WADW is the ICAO airport code for Umbu Mehang Kunda Airport in Indonesia.
  • D. DWD
    DWD is the three-letter National Rail station code for Dolwyddelan railway station in Wales.
  • E. #WAD
    #WAD is a commonly used social media hashtag for discussions, awareness campaigns, and events related to World AIDS Day and the global response to HIV/AIDS.
  • 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: WDA
Triple: [Zwickau district, vehicleRegistrationCode, WDA]
Generated description
WDA is a German vehicle registration code assigned to the Zwickau district in the state of Saxony.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WDA
Target entity description: WDA is a German vehicle registration code assigned to the Zwickau district in the state of Saxony.
  • A. Wda
    Wda is a river in northern Poland that flows through the Pomeranian region and is known for its scenic, forested course and popularity for kayaking and canoeing.
  • B. WDS
    WDS is the IATA airport code for Shiyan Wudangshan Airport, a regional airport serving the Shiyan and Wudangshan area in Hubei, China.
  • C. WADW
    WADW is the ICAO airport code for Umbu Mehang Kunda Airport in Indonesia.
  • D. DWD
    DWD is the three-letter National Rail station code for Dolwyddelan railway station in Wales.
  • E. #WAD
    #WAD is a commonly used social media hashtag for discussions, awareness campaigns, and events related to World AIDS Day and the global response to HIV/AIDS.
  • 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_69d86da4e86481909f1325fdc971b5ec completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1555e4ee48190a3b27b4ab9bdb1c8 completed April 16, 2026, 9:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffa945d9808190a65f5182db341393 completed May 9, 2026, 9:38 p.m.
NEDg Description generation batch_69ffaa8b03048190a3745df8a59fe066 completed May 9, 2026, 9:43 p.m.
NED2 Entity disambiguation (via description) batch_69ffab58e7e481908a13b739e0401b8b completed May 9, 2026, 9:47 p.m.
Created at: April 10, 2026, 4:50 a.m.