Triple

T1615584
Position Surface form Disambiguated ID Type / Status
Subject Silchar Airport E34709 entity
Predicate ICAO code P419 FINISHED
Object VEKU
VEKU is the ICAO airport code assigned to Silchar Airport in Assam, India.
 E182782 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: VEKU | Statement: [Silchar Airport, ICAO code, VEKU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: VEKU
Context triple: [Silchar Airport, ICAO code, VEKU]
  • A. Vajk
    Vajk was the original pagan name of Stephen I, the first Christian king and state-founder of Hungary.
  • B. Vuhovi
    Vuhovi is a locality in the Democratic Republic of the Congo known for being heavily affected during the 2018–2020 Kivu Ebola epidemic.
  • C. VE
    VE is the two-letter ISO 3166-1 alpha-2 country code assigned to Venezuela for international standardization and identification purposes.
  • D. Vestli
    Vestli is a residential neighborhood in the Stovner borough of Oslo, Norway, known for being served by the Oslo Metro.
  • E. VELO
    VELO is the high-precision vertex detector of the LHCb experiment at CERN, designed to measure particle trajectories very close to the proton–proton collision point.
  • 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: VEKU
Triple: [Silchar Airport, ICAO code, VEKU]
Generated description
VEKU is the ICAO airport code assigned to Silchar Airport in Assam, India.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: VEKU
Target entity description: VEKU is the ICAO airport code assigned to Silchar Airport in Assam, India.
  • A. Vajk
    Vajk was the original pagan name of Stephen I, the first Christian king and state-founder of Hungary.
  • B. Vuhovi
    Vuhovi is a locality in the Democratic Republic of the Congo known for being heavily affected during the 2018–2020 Kivu Ebola epidemic.
  • C. VE
    VE is the two-letter ISO 3166-1 alpha-2 country code assigned to Venezuela for international standardization and identification purposes.
  • D. Vestli
    Vestli is a residential neighborhood in the Stovner borough of Oslo, Norway, known for being served by the Oslo Metro.
  • E. VELO
    VELO is the high-precision vertex detector of the LHCb experiment at CERN, designed to measure particle trajectories very close to the proton–proton collision point.
  • 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_69a885ffc5ec819091afa325d5f9611c completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9099049e0819099763ecb09fb4f57 completed March 5, 2026, 4:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad51cd2e54819086924378792eb2e3 completed March 8, 2026, 10:39 a.m.
NEDg Description generation batch_69ad5248af2881909755ae87b4cd0041 completed March 8, 2026, 10:41 a.m.
NED2 Entity disambiguation (via description) batch_69ad52b3dcf081909e73fba891e985b2 completed March 8, 2026, 10:43 a.m.
Created at: March 4, 2026, 7:28 p.m.