Triple

T4644459
Position Surface form Disambiguated ID Type / Status
Subject Muswellbrook railway station E101730 entity
Predicate hasStationCode P1289 FINISHED
Object MBK
MBK is the station code for Muswellbrook railway station in New South Wales, Australia.
 E459286 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: MBK | Statement: [Muswellbrook railway station, hasStationCode, MBK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MBK
Context triple: [Muswellbrook railway station, hasStationCode, MBK]
  • A. MBK Center
    MBK Center is a large, popular shopping mall and entertainment complex in central Bangkok, Thailand, known for its wide range of affordable shops and bustling atmosphere.
  • B. MBN
    MBN is a U.S.-government-funded media organization that operates Arabic-language television, radio, and digital news services targeting audiences in the Middle East and North Africa.
  • C. MBZ
    MBZ is the widely used acronym for Mohamed bin Zayed Al Nahyan, the President of the United Arab Emirates and Ruler of Abu Dhabi.
  • D. MYK
    MYK is the vehicle registration code for the district of Mayen-Koblenz in the German state of Rhineland-Palatinate.
  • E. KMK
    KMK is the central coordinating body of Germany’s state education and cultural ministers, responsible for harmonizing policies across the federal states.
  • 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: MBK
Triple: [Muswellbrook railway station, hasStationCode, MBK]
Generated description
MBK is the station code for Muswellbrook railway station in New South Wales, Australia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MBK
Target entity description: MBK is the station code for Muswellbrook railway station in New South Wales, Australia.
  • A. MBK Center
    MBK Center is a large, popular shopping mall and entertainment complex in central Bangkok, Thailand, known for its wide range of affordable shops and bustling atmosphere.
  • B. MBN
    MBN is a U.S.-government-funded media organization that operates Arabic-language television, radio, and digital news services targeting audiences in the Middle East and North Africa.
  • C. MBZ
    MBZ is the widely used acronym for Mohamed bin Zayed Al Nahyan, the President of the United Arab Emirates and Ruler of Abu Dhabi.
  • D. MYK
    MYK is the vehicle registration code for the district of Mayen-Koblenz in the German state of Rhineland-Palatinate.
  • E. KMK
    KMK is the central coordinating body of Germany’s state education and cultural ministers, responsible for harmonizing policies across the federal states.
  • 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_69bd43d3bc7c81908f81fcf380476b0f completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd6236e5488190a0ed6991c65c0a74 completed March 20, 2026, 3:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfadc5dc081908d56a49895105efb completed March 21, 2026, 1:56 a.m.
NEDg Description generation batch_69bdfc6751988190917ec53a8e2e27ec completed March 21, 2026, 2:03 a.m.
NED2 Entity disambiguation (via description) batch_69be009e6c488190b18e1b2b4b34ecef completed March 21, 2026, 2:21 a.m.
Created at: March 20, 2026, 1:14 p.m.