Triple

T14163687
Position Surface form Disambiguated ID Type / Status
Subject Secunderabad Junction E351012 entity
Predicate hasStationCode P1289 FINISHED
Object SC
SC is the Indian Railways station code for Secunderabad Junction, a major railway hub in Hyderabad, Telangana.
 E351012 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: SC | Statement: [Secunderabad Junction, hasStationCode, SC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SC
Context triple: [Secunderabad Junction, hasStationCode, SC]
  • A. SC
    SC is the standard two-letter postal abbreviation for the U.S. state of South Carolina.
  • B. SC
    SC is the vehicle registration code used on license plates for the German town of Schwabach in Bavaria.
  • C. SC
    SC is the vehicle registration code used on license plates for vehicles registered in Częstochowa, a city in southern Poland.
  • D. SC
    SC is the commonly used abbreviation for Service Canada, the federal government agency that delivers a wide range of public services and benefits to Canadians.
  • E. SC
    SC is the official abbreviation used by the United States Navy to denote officers of its Supply Corps, the branch responsible for logistics, supply, and financial management.
  • 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: SC
Triple: [Secunderabad Junction, hasStationCode, SC]
Generated description
SC is the Indian Railways station code for Secunderabad Junction, a major railway hub in Hyderabad, Telangana.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SC
Target entity description: SC is the Indian Railways station code for Secunderabad Junction, a major railway hub in Hyderabad, Telangana.
  • A. SC chosen
    SC is the official Indian Railways station code for Secunderabad Junction, a major railway hub in Telangana, India.
  • B. SC
    SC is the vehicle registration code used on license plates for vehicles registered in Częstochowa, a city in southern Poland.
  • C. SC
    SC is the vehicle registration code used on license plates for the German town of Schwabach in Bavaria.
  • D. SC
    SC is the commonly used abbreviation for Service Canada, the federal government agency that delivers a wide range of public services and benefits to Canadians.
  • E. SC
    SC is the standard two-letter postal abbreviation for the U.S. state of South Carolina.
  • F. None of above.

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_69d8278775fc8190b0802d22ca2f495d completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de613a4a2081908fd51bf4b4d82b6c completed April 14, 2026, 3:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcf7f3170481909f3981c1e56235d9 completed May 7, 2026, 8:37 p.m.
NEDg Description generation batch_69fcfe9debe08190b9943f941f1b8813 completed May 7, 2026, 9:05 p.m.
NED2 Entity disambiguation (via description) batch_69fcff29f7608190b4b7d24fc1e011bf completed May 7, 2026, 9:07 p.m.
Created at: April 10, 2026, 12:59 a.m.