Triple

T14542186
Position Surface form Disambiguated ID Type / Status
Subject Vandalur railway station E341195 entity
Predicate hasStationCode P1289 FINISHED
Object VDR
VDR is the station code assigned to Vandalur railway station in the Chennai Suburban Railway network in India.
 E1105499 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: VDR | Statement: [Vandalur railway station, hasStationCode, VDR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: VDR
Context triple: [Vandalur railway station, hasStationCode, VDR]
  • A. VDP
    VDP is a networking protocol used to automatically discover and configure virtual devices or ports in virtualized environments.
  • B. VCDR
    VCDR is the commonly used abbreviation for the Vienna Convention on Diplomatic Relations, the key international treaty that defines the framework for diplomatic relations between independent countries.
  • C. VRD
    VRD is the ICAO airline designator used to identify Virgin America in aviation operations and communications.
  • D. VDS
    VDS is the IATA airport code for Vadsø Airport in Norway.
  • E. VDV
    VDV is the elite airborne branch of Russia’s armed forces, known for rapid-deployment paratrooper and air-assault operations.
  • 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: VDR
Triple: [Vandalur railway station, hasStationCode, VDR]
Generated description
VDR is the station code assigned to Vandalur railway station in the Chennai Suburban Railway network in India.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: VDR
Target entity description: VDR is the station code assigned to Vandalur railway station in the Chennai Suburban Railway network in India.
  • A. VDP
    VDP is a networking protocol used to automatically discover and configure virtual devices or ports in virtualized environments.
  • B. VCDR
    VCDR is the commonly used abbreviation for the Vienna Convention on Diplomatic Relations, the key international treaty that defines the framework for diplomatic relations between independent countries.
  • C. VRD
    VRD is the ICAO airline designator used to identify Virgin America in aviation operations and communications.
  • D. VDS
    VDS is the IATA airport code for Vadsø Airport in Norway.
  • E. VDV
    VDV is the elite airborne branch of Russia’s armed forces, known for rapid-deployment paratrooper and air-assault operations.
  • 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_69d822db9c8481908213ceb39585f792 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb1be5a8081909bf727e28a5bba4a completed April 14, 2026, 9:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd7a5eb85c8190a0c1696b63ddf8e1 completed May 8, 2026, 5:53 a.m.
NEDg Description generation batch_69fd7d7245808190b30d591407731bd5 completed May 8, 2026, 6:06 a.m.
NED2 Entity disambiguation (via description) batch_69fd7dfc22008190a2c37bed8fd8d21a completed May 8, 2026, 6:09 a.m.
Created at: April 10, 2026, 1:22 a.m.