Triple

T20395107
Position Surface form Disambiguated ID Type / Status
Subject Notodden stasjon E500180 entity
Predicate hasStationCode P1289 FINISHED
Object NTD
NTD is the station code for Notodden Station, a railway station in Notodden, Norway.
 E376115 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: NTD | Statement: [Notodden stasjon, hasStationCode, NTD]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: NTD
Context triple: [Notodden stasjon, hasStationCode, NTD]
  • A. NTD
    NTD is the currency code commonly used to denote the New Taiwan dollar, the official monetary unit of Taiwan.
  • B. NTM
    NTM is the abbreviation for the National Taiwan Museum, a major public museum in Taipei dedicated to Taiwan’s natural history and cultural heritage.
  • C. NTF
    NTF is a high-speed wind tunnel facility operated by NASA for advanced aerodynamic testing at transonic speeds.
  • D. NTZ
    NTZ is the commonly used abbreviation for the Lamlash Bay no-take marine conservation zone off the Isle of Arran in Scotland.
  • E. NGTB
    NGTB is the ICAO airport code for Abemama Atoll Airport in Kiribati, serving the island of Abemama in the central Pacific.
  • 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: NTD
Triple: [Notodden stasjon, hasStationCode, NTD]
Generated description
NTD is the station code for Notodden Station, a railway station in Notodden, Norway.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: NTD
Target entity description: NTD is the station code for Notodden Station, a railway station in Notodden, Norway.
  • A. NTD chosen
    NTD is the currency code commonly used to denote the New Taiwan dollar, the official monetary unit of Taiwan.
  • B. NTM
    NTM is the abbreviation for the National Taiwan Museum, a major public museum in Taipei dedicated to Taiwan’s natural history and cultural heritage.
  • C. NTF
    NTF is a high-speed wind tunnel facility operated by NASA for advanced aerodynamic testing at transonic speeds.
  • D. NTZ
    NTZ is the commonly used abbreviation for the Lamlash Bay no-take marine conservation zone off the Isle of Arran in Scotland.
  • E. NGTB
    NGTB is the ICAO airport code for Abemama Atoll Airport in Kiribati, serving the island of Abemama in the central Pacific.
  • F. None of above.

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_69e0b4a71ebc8190b153a36c738730f4 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e67912d7948190ac2fda8ce95e5c70 completed April 20, 2026, 7:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a08762804ac81909e90e7983246cb28 completed May 16, 2026, 1:50 p.m.
NEDg Description generation batch_6a0877d6b364819080b5e701acea02aa completed May 16, 2026, 1:57 p.m.
NED2 Entity disambiguation (via description) batch_6a08787cfe6c8190881554ead3cfd248 completed May 16, 2026, 2 p.m.
Created at: April 16, 2026, 11:28 a.m.