Triple

T11322211
Position Surface form Disambiguated ID Type / Status
Subject Vashi E268120 entity
Predicate hasStationCode P1289 FINISHED
Object VSH
VSH is the Indian Railways station code for Vashi railway station, a key suburban rail stop in Navi Mumbai, Maharashtra.
 E919120 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: VSH | Statement: [Vashi, hasStationCode, VSH]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: VSH
Context triple: [Vashi, hasStationCode, VSH]
  • A. VSL
    VSL is the station code for Venezia Santa Lucia, the main railway terminal serving the historic center of Venice, Italy.
  • B. VSI
    VSI is the commonly used abbreviation for the "Very Short Introductions" series of concise, authoritative books published by Oxford University Press on a wide range of subjects.
  • C. VŠE
    VŠE is the commonly used abbreviation for the University of Economics in Prague, a leading Czech institution specializing in economics and business studies.
  • D. VES
    VES is an abbreviation for the Virtual Execution System, a runtime environment designed to execute managed code in a platform-independent manner.
  • E. SVH
    SVH is the FAA location identifier for Stanly County Airport, a public-use airport serving Stanly County, North Carolina.
  • 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: VSH
Triple: [Vashi, hasStationCode, VSH]
Generated description
VSH is the Indian Railways station code for Vashi railway station, a key suburban rail stop in Navi Mumbai, Maharashtra.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: VSH
Target entity description: VSH is the Indian Railways station code for Vashi railway station, a key suburban rail stop in Navi Mumbai, Maharashtra.
  • A. VSL
    VSL is the station code for Venezia Santa Lucia, the main railway terminal serving the historic center of Venice, Italy.
  • B. VSI
    VSI is the commonly used abbreviation for the "Very Short Introductions" series of concise, authoritative books published by Oxford University Press on a wide range of subjects.
  • C. VŠE
    VŠE is the commonly used abbreviation for the University of Economics in Prague, a leading Czech institution specializing in economics and business studies.
  • D. VES
    VES is an abbreviation for the Virtual Execution System, a runtime environment designed to execute managed code in a platform-independent manner.
  • E. SVH
    SVH is the FAA location identifier for Stanly County Airport, a public-use airport serving Stanly County, North Carolina.
  • 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_69d6aaca5c24819083db46a30d86cb34 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9dff37081909622623e66e17ccd completed April 9, 2026, 6:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69e525ed950081908ec94cfbf8849e85 completed April 19, 2026, 6:58 p.m.
NEDg Description generation batch_69e52c82b6108190aec9b6e9d726f803 completed April 19, 2026, 7:26 p.m.
NED2 Entity disambiguation (via description) batch_69e531b079708190ac9e19127d36a848 completed April 19, 2026, 7:49 p.m.
Created at: April 8, 2026, 9:32 p.m.