Triple

T6196578
Position Surface form Disambiguated ID Type / Status
Subject Northampton railway station E138522 entity
Predicate stationCode P1289 FINISHED
Object NMP
NMP is the three-letter National Rail station code assigned to Northampton railway station in Northampton, England.
 E574874 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: NMP | Statement: [Northampton railway station, stationCode, NMP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: NMP
Context triple: [Northampton railway station, stationCode, NMP]
  • A. NVP
    NVP is the official station code for Nieuw-Vennep railway station in the Netherlands.
  • B. NMB
    NMB is a German vehicle registration code assigned to the Burgenlandkreis district in the state of Saxony-Anhalt.
  • C. NMTI
    NMTI is a prestigious United States presidential award that honors individuals, teams, and companies for outstanding contributions to technological innovation and advancement.
  • D. NMTI
    NMTI is an acronym whose specific meaning depends on context, commonly referring to various technical or institutional names.
  • E. MNP
    MNP is the three-letter ISO 3166-1 alpha-3 country code assigned to the Northern Mariana Islands.
  • 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: NMP
Triple: [Northampton railway station, stationCode, NMP]
Generated description
NMP is the three-letter National Rail station code assigned to Northampton railway station in Northampton, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: NMP
Target entity description: NMP is the three-letter National Rail station code assigned to Northampton railway station in Northampton, England.
  • A. NVP
    NVP is the official station code for Nieuw-Vennep railway station in the Netherlands.
  • B. NMB
    NMB is a German vehicle registration code assigned to the Burgenlandkreis district in the state of Saxony-Anhalt.
  • C. NMTI
    NMTI is a prestigious United States presidential award that honors individuals, teams, and companies for outstanding contributions to technological innovation and advancement.
  • D. NMTI
    NMTI is an acronym whose specific meaning depends on context, commonly referring to various technical or institutional names.
  • E. MNP
    MNP is the three-letter ISO 3166-1 alpha-3 country code assigned to the Northern Mariana Islands.
  • 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_69c008ab9b3081908a11b2c744838435 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062508f5c8190a00291708a9a7de9 completed March 22, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c16f2a40a88190847f607a6e2c5f4e completed March 23, 2026, 4:49 p.m.
NEDg Description generation batch_69c1d232ab1881909cc3014beb664446 completed March 23, 2026, 11:52 p.m.
NED2 Entity disambiguation (via description) batch_69c1d2c532988190a98f615638987159 completed March 23, 2026, 11:54 p.m.
Created at: March 22, 2026, 4:20 p.m.