Triple

T13157306
Position Surface form Disambiguated ID Type / Status
Subject Ghaziabad Junction railway station E312622 entity
Predicate stationCode P1289 FINISHED
Object GZB
GZB is the station code for Ghaziabad Junction, a major railway hub in the Indian state of Uttar Pradesh.
 E1024528 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: GZB | Statement: [Ghaziabad Junction railway station, stationCode, GZB]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: GZB
Context triple: [Ghaziabad Junction railway station, stationCode, GZB]
  • A. ZGB
    ZGB is the abbreviation for the Swiss Civil Code, the fundamental body of private law governing civil matters in Switzerland.
  • B. GZT
    GZT is the IATA airport code for Oğuzeli Airport serving Gaziantep in southeastern Turkey.
  • C. GZ
    GZ is the vehicle registration code used on license plates for the district of Günzburg in Bavaria, Germany.
  • D. GZQ
    GZQ is the station code used to identify Guangzhou Railway Station, a major rail transport hub in Guangzhou, China.
  • E. GZM
    GZM is a major metropolitan area, often referring to the Upper Silesian–Zagłębie Metropolis in southern Poland, encompassing a large urban and industrial region.
  • 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: GZB
Triple: [Ghaziabad Junction railway station, stationCode, GZB]
Generated description
GZB is the station code for Ghaziabad Junction, a major railway hub in the Indian state of Uttar Pradesh.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: GZB
Target entity description: GZB is the station code for Ghaziabad Junction, a major railway hub in the Indian state of Uttar Pradesh.
  • A. ZGB
    ZGB is the abbreviation for the Swiss Civil Code, the fundamental body of private law governing civil matters in Switzerland.
  • B. GZT
    GZT is the IATA airport code for Oğuzeli Airport serving Gaziantep in southeastern Turkey.
  • C. GZ
    GZ is the vehicle registration code used on license plates for the district of Günzburg in Bavaria, Germany.
  • D. GZQ
    GZQ is the station code used to identify Guangzhou Railway Station, a major rail transport hub in Guangzhou, China.
  • E. GZM
    GZM is a major metropolitan area, often referring to the Upper Silesian–Zagłębie Metropolis in southern Poland, encompassing a large urban and industrial region.
  • 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_69d806aabde48190899e13e41659cae5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c084028819093bc4e94d53b4f17 completed April 10, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6eaf06f408190949f9ed5e899815b completed May 3, 2026, 6:28 a.m.
NEDg Description generation batch_69f6f07d52788190a39bc4fe049bcf5e completed May 3, 2026, 6:51 a.m.
NED2 Entity disambiguation (via description) batch_69f6f0d6eb2c81908463125a922edc9c completed May 3, 2026, 6:53 a.m.
Created at: April 9, 2026, 9:12 p.m.