Triple

T14026397
Position Surface form Disambiguated ID Type / Status
Subject Jolly Grant Airport, Dehradun E337467 entity
Predicate ICAOcode P419 FINISHED
Object VIDN
VIDN is the ICAO airport code for Jolly Grant Airport serving Dehradun in the Indian state of Uttarakhand.
E1075887 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: VIDN | Statement: [Jolly Grant Airport, Dehradun, ICAOcode, VIDN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: VIDN
Context triple: [Jolly Grant Airport, Dehradun, ICAOcode, VIDN]
  • A. VIDN
    VIDN is the four-letter ICAO airport code assigned to Noida International Airport in Uttar Pradesh, India.
  • B. VIDO
    VIDO is a Canadian research organization at the University of Saskatchewan specializing in vaccine development and infectious disease research for both humans and animals.
  • C. Vdio
    Vdio was an online video-on-demand and streaming service launched by Skype and Rdio co-founder Janus Friis as an attempt to compete with platforms like Netflix.
  • D. VIDP
    VIDP is the ICAO airport code for Indira Gandhi International Airport, the primary international aviation hub serving New Delhi, India.
  • E. Viddy
    Viddy was a mobile social video-sharing app that allowed users to create, edit, and share short video clips with an online community.
  • 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: VIDN
Triple: [Jolly Grant Airport, Dehradun, ICAOcode, VIDN]
Generated description
VIDN is the ICAO airport code for Jolly Grant Airport serving Dehradun in the Indian state of Uttarakhand.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: VIDN
Target entity description: VIDN is the ICAO airport code for Jolly Grant Airport serving Dehradun in the Indian state of Uttarakhand.
  • A. VIDN
    VIDN is the four-letter ICAO airport code assigned to Noida International Airport in Uttar Pradesh, India.
  • B. VIDO
    VIDO is a Canadian research organization at the University of Saskatchewan specializing in vaccine development and infectious disease research for both humans and animals.
  • C. Vdio
    Vdio was an online video-on-demand and streaming service launched by Skype and Rdio co-founder Janus Friis as an attempt to compete with platforms like Netflix.
  • D. VIDP
    VIDP is the ICAO airport code for Indira Gandhi International Airport, the primary international aviation hub serving New Delhi, India.
  • E. Viddy
    Viddy was a mobile social video-sharing app that allowed users to create, edit, and share short video clips with an online community.
  • 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_69d81c6543a48190bd5ba93d7419e797 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2fa830ac81908cb7df7c9e81e42a completed April 14, 2026, 12:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbc333b7a08190b4f121fef69f7513 completed May 6, 2026, 10:39 p.m.
NEDg Description generation batch_69fc438f85308190ae917812686006f6 completed May 7, 2026, 7:47 a.m.
NED2 Entity disambiguation (via description) batch_69fc444a30a48190a2f65afcd5424d14 completed May 7, 2026, 7:50 a.m.
Created at: April 9, 2026, 10:20 p.m.