Triple

T8773815
Position Surface form Disambiguated ID Type / Status
Subject Visakhapatnam railway station E208527 entity
Predicate hasStationCode P1289 FINISHED
Object VSKP
VSKP is the station code for Visakhapatnam railway station, a major rail hub in the coastal city of Visakhapatnam, India.
 E756268 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: VSKP | Statement: [Visakhapatnam railway station, hasStationCode, VSKP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: VSKP
Context triple: [Visakhapatnam railway station, hasStationCode, VSKP]
  • A. VKSU
    VKSU is a public university located in Ara, Bihar, India, offering undergraduate and postgraduate programs across various disciplines.
  • B. KSPU
    KSPU is a Ukrainian higher education institution specializing in teacher training and pedagogical studies, located in Kryvyi Rih.
  • C. KAVP
    KAVP is the ICAO airport code for Wilkes-Barre/Scranton International Airport in Pennsylvania, United States.
  • D. KVP
    KVP (Katholieke Volkspartij) was a major Dutch Catholic political party that played a central role in post–World War II Dutch politics before merging into the Christian Democratic Appeal (CDA).
  • E. VSP
    VSP is the primary statewide law enforcement agency responsible for highway patrol, criminal investigations, and public safety in the Commonwealth of Virginia.
  • 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: VSKP
Triple: [Visakhapatnam railway station, hasStationCode, VSKP]
Generated description
VSKP is the station code for Visakhapatnam railway station, a major rail hub in the coastal city of Visakhapatnam, India.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: VSKP
Target entity description: VSKP is the station code for Visakhapatnam railway station, a major rail hub in the coastal city of Visakhapatnam, India.
  • A. VKSU
    VKSU is a public university located in Ara, Bihar, India, offering undergraduate and postgraduate programs across various disciplines.
  • B. KSPU
    KSPU is a Ukrainian higher education institution specializing in teacher training and pedagogical studies, located in Kryvyi Rih.
  • C. KAVP
    KAVP is the ICAO airport code for Wilkes-Barre/Scranton International Airport in Pennsylvania, United States.
  • D. KVP
    KVP (Katholieke Volkspartij) was a major Dutch Catholic political party that played a central role in post–World War II Dutch politics before merging into the Christian Democratic Appeal (CDA).
  • E. VSP
    VSP is the primary statewide law enforcement agency responsible for highway patrol, criminal investigations, and public safety in the Commonwealth of Virginia.
  • 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_69ca835edb4481909b4aafb616dc5eb7 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5f2ef3288190988bd69e8a02e741 completed March 31, 2026, 11:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf51c760b48190b2138cd2861b2c61 completed April 3, 2026, 5:36 a.m.
NEDg Description generation batch_69cf52f0886881909ceb9fbe54f84d11 completed April 3, 2026, 5:41 a.m.
NED2 Entity disambiguation (via description) batch_69cf53bc19fc81908f43c3fa29bae021 completed April 3, 2026, 5:44 a.m.
Created at: March 30, 2026, 6:41 p.m.