Triple

T16566091
Position Surface form Disambiguated ID Type / Status
Subject Gare de Lorraine TGV E402462 entity
Predicate stationCode P1289 FINISHED
Object XZI
XZI is the railway station code used to identify Gare de Lorraine TGV, a high-speed train station in northeastern France.
 E1221909 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: XZI | Statement: [Gare de Lorraine TGV, stationCode, XZI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: XZI
Context triple: [Gare de Lorraine TGV, stationCode, XZI]
  • A. xz
    xz is a modern lossless data compression format and toolset based on the LZMA algorithm, known for achieving high compression ratios and commonly used for software distribution and archival on Unix-like systems.
  • B. XUZ
    XUZ is the IATA airport code for Xuzhou Guanyin International Airport, a commercial airport serving the city of Xuzhou in Jiangsu Province, China.
  • C. IXZ
    IXZ is the IATA airport code for Veer Savarkar International Airport serving Port Blair in the Andaman and Nicobar Islands, India.
  • D. ZI
    ZI is the vehicle registration code used on license plates for vehicles registered in the district of Görlitz in Germany.
  • E. ZSXZ
    ZSXZ is the ICAO airport code assigned to Xuzhou Guanyin International Airport in Xuzhou, Jiangsu Province, China.
  • 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: XZI
Triple: [Gare de Lorraine TGV, stationCode, XZI]
Generated description
XZI is the railway station code used to identify Gare de Lorraine TGV, a high-speed train station in northeastern France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: XZI
Target entity description: XZI is the railway station code used to identify Gare de Lorraine TGV, a high-speed train station in northeastern France.
  • A. xz
    xz is a modern lossless data compression format and toolset based on the LZMA algorithm, known for achieving high compression ratios and commonly used for software distribution and archival on Unix-like systems.
  • B. XUZ
    XUZ is the IATA airport code for Xuzhou Guanyin International Airport, a commercial airport serving the city of Xuzhou in Jiangsu Province, China.
  • C. IXZ
    IXZ is the IATA airport code for Veer Savarkar International Airport serving Port Blair in the Andaman and Nicobar Islands, India.
  • D. ZI
    ZI is the vehicle registration code used on license plates for vehicles registered in the district of Görlitz in Germany.
  • E. ZSXZ
    ZSXZ is the ICAO airport code assigned to Xuzhou Guanyin International Airport in Xuzhou, Jiangsu Province, China.
  • 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_69d8838648088190acf97ef11fc3f61b completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e35772255881909f737da89bcd06b8 completed April 18, 2026, 10:05 a.m.
NED1 Entity disambiguation (via context triple) batch_6a006ee1c1d0819096367344e48bd8d0 completed May 10, 2026, 11:41 a.m.
NEDg Description generation batch_6a006fba728c8190a835ce72a15563e1 completed May 10, 2026, 11:44 a.m.
NED2 Entity disambiguation (via description) batch_6a0070aee0248190b3463b98a739d1ae completed May 10, 2026, 11:49 a.m.
Created at: April 10, 2026, 5:15 a.m.