Triple

T11552109
Position Surface form Disambiguated ID Type / Status
Subject Bromsgrove railway station E273921 entity
Predicate hasStationCode P1289 FINISHED
Object BMV
BMV is the National Rail station code for Bromsgrove railway station in Worcestershire, England.
 E932723 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: BMV | Statement: [Bromsgrove railway station, hasStationCode, BMV]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BMV
Context triple: [Bromsgrove railway station, hasStationCode, BMV]
  • A. BMV
    BMV is the main stock exchange in Mexico, serving as the country’s central marketplace for trading equities and other financial instruments.
  • B. BMVg
    BMVg is the commonly used abbreviation for Germany’s Federal Ministry of Defence, the government department responsible for the country’s military and defense policy.
  • C. BMVI
    BMVI is the abbreviation for Germany’s former Federal Ministry responsible for transport policy and digital infrastructure development.
  • D. BMVI
    BMVI is an EU funding instrument focused on strengthening border management and visa policy implementation across member states.
  • E. BMJV
    BMJV was the former abbreviation for Germany’s Federal Ministry of Justice, used before its name change and rebranding.
  • 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: BMV
Triple: [Bromsgrove railway station, hasStationCode, BMV]
Generated description
BMV is the National Rail station code for Bromsgrove railway station in Worcestershire, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BMV
Target entity description: BMV is the National Rail station code for Bromsgrove railway station in Worcestershire, England.
  • A. BMV
    BMV is the main stock exchange in Mexico, serving as the country’s central marketplace for trading equities and other financial instruments.
  • B. BMVg
    BMVg is the commonly used abbreviation for Germany’s Federal Ministry of Defence, the government department responsible for the country’s military and defense policy.
  • C. BMVI
    BMVI is the abbreviation for Germany’s former Federal Ministry responsible for transport policy and digital infrastructure development.
  • D. BMVI
    BMVI is an EU funding instrument focused on strengthening border management and visa policy implementation across member states.
  • E. BMJV
    BMJV was the former abbreviation for Germany’s Federal Ministry of Justice, used before its name change and rebranding.
  • 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_69d6aae4dfa48190a3ab0b19a159a3c5 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d88a83f1e88190aabf11a4c8a6c9e5 completed April 10, 2026, 5:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69e6e8396ed081909bdf381db3dacd62 completed April 21, 2026, 3 a.m.
NEDg Description generation batch_69e6ef93e7d88190af3853b82de23c1b completed April 21, 2026, 3:31 a.m.
NED2 Entity disambiguation (via description) batch_69e6f9144afc819081ee7f78e32ad39a completed April 21, 2026, 4:12 a.m.
Created at: April 8, 2026, 9:37 p.m.