Triple

T4535674
Position Surface form Disambiguated ID Type / Status
Subject Sunderland, United Kingdom E107401 entity
Predicate postalCodeArea P920 FINISHED
Object SR
SR is the postcode area in North East England that covers Sunderland and surrounding parts of Tyne and Wear and County Durham.
 E450766 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: SR | Statement: [Sunderland, United Kingdom, postalCodeArea, SR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SR
Context triple: [Sunderland, United Kingdom, postalCodeArea, SR]
  • A. SR
    SR is the two-letter ISO 3166-1 alpha-2 country code assigned to Suriname.
  • B. SV
    SV is the official abbreviation for the Slovenian Armed Forces, the military organization responsible for defending the Republic of Slovenia.
  • C. SV
    SV is the two-letter ISO 3166-1 alpha-2 country code assigned to El Salvador.
  • D. SV
    SV is the commonly used abbreviation for the Faculty of Social Sciences at the University of Oslo, encompassing disciplines such as sociology, political science, economics, and related fields.
  • E. RS
    RS is a sporty, performance-oriented trim level of the Chevrolet Trailblazer that features distinctive styling and upgraded features.
  • 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: SR
Triple: [Sunderland, United Kingdom, postalCodeArea, SR]
Generated description
SR is the postcode area in North East England that covers Sunderland and surrounding parts of Tyne and Wear and County Durham.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SR
Target entity description: SR is the postcode area in North East England that covers Sunderland and surrounding parts of Tyne and Wear and County Durham.
  • A. SR
    SR is the two-letter ISO 3166-1 alpha-2 country code assigned to Suriname.
  • B. SV
    SV is the two-letter ISO 3166-1 alpha-2 country code assigned to El Salvador.
  • C. SV
    SV is the commonly used abbreviation for the Faculty of Social Sciences at the University of Oslo, encompassing disciplines such as sociology, political science, economics, and related fields.
  • D. SV
    SV is the official abbreviation for the Slovenian Armed Forces, the military organization responsible for defending the Republic of Slovenia.
  • E. RS
    RS is a sporty, performance-oriented trim level of the Chevrolet Trailblazer that features distinctive styling and upgraded features.
  • 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_69bd43f922788190b7edfa294e39b178 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd57b634b08190845d04213cf8d5b9 completed March 20, 2026, 2:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdacf016d0819080665256c84d37a3 completed March 20, 2026, 8:24 p.m.
NEDg Description generation batch_69bdad81ace48190956f8f62610e188d completed March 20, 2026, 8:26 p.m.
NED2 Entity disambiguation (via description) batch_69bdadb912148190bf4390c31396f189 completed March 20, 2026, 8:27 p.m.
Created at: March 20, 2026, 1:04 p.m.