Triple

T11763097
Position Surface form Disambiguated ID Type / Status
Subject Volkstheater U-Bahn station E279703 entity
Predicate hasStationCode P1289 FINISHED
Object VOT
VOT is the station code used to identify the Volkstheater U-Bahn station in the Vienna public transport network.
E943905 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: VOT | Statement: [Volkstheater U-Bahn station, hasStationCode, VOT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: VOT
Context triple: [Volkstheater U-Bahn station, hasStationCode, VOT]
  • A. VOW
    VOW is the primary stock ticker for Volkswagen AG shares listed on the Frankfurt Stock Exchange.
  • B. VOTV
    VOTV is the ICAO airport code for Trivandrum International Airport, a major airport serving Thiruvananthapuram in the Indian state of Kerala.
  • C. VOCI
    VOCI is the ICAO airport code for Cochin International Airport in Kochi, India, a major international gateway in the state of Kerala.
  • D. VOTP
    VOTP is the ICAO airport code assigned to Tirupati Airport in Andhra Pradesh, India.
  • E. VOZ
    VOZ is the IATA airport code for Voronezh Peter the Great Airport in Voronezh, Russia.
  • 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: VOT
Triple: [Volkstheater U-Bahn station, hasStationCode, VOT]
Generated description
VOT is the station code used to identify the Volkstheater U-Bahn station in the Vienna public transport network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: VOT
Target entity description: VOT is the station code used to identify the Volkstheater U-Bahn station in the Vienna public transport network.
  • A. VOW
    VOW is the primary stock ticker for Volkswagen AG shares listed on the Frankfurt Stock Exchange.
  • B. VOTV
    VOTV is the ICAO airport code for Trivandrum International Airport, a major airport serving Thiruvananthapuram in the Indian state of Kerala.
  • C. VOCI
    VOCI is the ICAO airport code for Cochin International Airport in Kochi, India, a major international gateway in the state of Kerala.
  • D. VOTP
    VOTP is the ICAO airport code assigned to Tirupati Airport in Andhra Pradesh, India.
  • E. VOZ
    VOZ is the IATA airport code for Voronezh Peter the Great Airport in Voronezh, Russia.
  • 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_69d6ab01d2688190ad8ed6bda487eaa5 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a5248e0881909ed1b4df7be422f7 completed April 10, 2026, 7:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69f01a570ca88190ba2f3791c0e0ba60 completed April 28, 2026, 2:24 a.m.
NEDg Description generation batch_69f043b3c51c8190a764433e86f1333e completed April 28, 2026, 5:20 a.m.
NED2 Entity disambiguation (via description) batch_69f05b04d7248190b8ec4be4f2c3e388 completed April 28, 2026, 7 a.m.
Created at: April 8, 2026, 9:41 p.m.