Triple

T22993374
Position Surface form Disambiguated ID Type / Status
Subject Banaras railway station E572116 entity
Predicate stationCode P1289 FINISHED
Object BSBS
BSBS is the station code for Banaras railway station, a major rail hub serving the city of Varanasi in Uttar Pradesh, India.
 E1564481 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: BSBS | Statement: [Banaras railway station, stationCode, BSBS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BSBS
Context triple: [Banaras railway station, stationCode, BSBS]
  • A. Bs
    Bs is the currency symbol used to denote the Bolivian boliviano, the official monetary unit of Bolivia.
  • B. BS
    BS was the stock ticker symbol for Bethlehem Steel Corporation, once one of the largest and most influential steel producers in the United States.
  • C. BS
    BS is the designation used for British Standards, the national standards published by BSI Group in the United Kingdom.
  • D. BS
    BS is the vehicle registration code used on license plates for the Swiss canton of Basel-Stadt.
  • E. BS
    BS is the official vehicle registration code used on license plates for the German city of Braunschweig.
  • 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: BSBS
Triple: [Banaras railway station, stationCode, BSBS]
Generated description
BSBS is the station code for Banaras railway station, a major rail hub serving the city of Varanasi in Uttar Pradesh, India.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BSBS
Target entity description: BSBS is the station code for Banaras railway station, a major rail hub serving the city of Varanasi in Uttar Pradesh, India.
  • A. Bs
    Bs is the currency symbol used to denote the Bolivian boliviano, the official monetary unit of Bolivia.
  • B. BS
    BS was the stock ticker symbol for Bethlehem Steel Corporation, once one of the largest and most influential steel producers in the United States.
  • C. BS
    BS is the designation used for British Standards, the national standards published by BSI Group in the United Kingdom.
  • D. BS
    BS is the vehicle registration code used on license plates for the Swiss canton of Basel-Stadt.
  • E. BS
    BS is the official vehicle registration code used on license plates for the German city of Braunschweig.
  • 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_69e245b535808190adef8a9df3c584db completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f182f1940c8190a5645ee8d8e5e063 completed April 29, 2026, 4:02 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0bd37b1a0c819086bf665e96c2a540 completed May 19, 2026, 3:05 a.m.
NEDg Description generation batch_6a0bd44a4434819093871158e49bafbc completed May 19, 2026, 3:08 a.m.
NED2 Entity disambiguation (via description) batch_6a0bd4e53024819084592e995cc902e7 completed May 19, 2026, 3:11 a.m.
Created at: April 17, 2026, 3:50 p.m.