Triple

T1214673
Position Surface form Disambiguated ID Type / Status
Subject Staines-upon-Thames E26080 entity
Predicate hasPostcodeArea P920 FINISHED
Object TW
TW is a UK postcode area in southwest London and parts of Surrey, covering towns such as Twickenham and Staines-upon-Thames.
 E140097 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: TW | Statement: [Staines-upon-Thames, hasPostcodeArea, TW]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TW
Context triple: [Staines-upon-Thames, hasPostcodeArea, TW]
  • A. TW
    TW is the two-letter ISO 3166 country code assigned to Taiwan (commonly referred to as Chinese Taipei in certain international contexts).
  • B. TR
    TR is the two-letter ISO 3166-1 alpha-2 country code assigned to Turkey for international standardization and referencing.
  • C. TOR
    TOR is the standard three-letter abbreviation used to represent the Toronto Maple Leafs in sports standings, statistics, and media.
  • D. TH
    TH is the two-letter ISO 3166-1 alpha-2 country code assigned to Thailand for international standardization and identification.
  • E. TM
    TM is the New York Stock Exchange ticker symbol for Toyota Motor Corporation, the Japanese multinational automotive manufacturer.
  • 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: TW
Triple: [Staines-upon-Thames, hasPostcodeArea, TW]
Generated description
TW is a UK postcode area in southwest London and parts of Surrey, covering towns such as Twickenham and Staines-upon-Thames.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TW
Target entity description: TW is a UK postcode area in southwest London and parts of Surrey, covering towns such as Twickenham and Staines-upon-Thames.
  • A. TW
    TW is the two-letter ISO 3166 country code assigned to Taiwan (commonly referred to as Chinese Taipei in certain international contexts).
  • B. TR
    TR is the two-letter ISO 3166-1 alpha-2 country code assigned to Turkey for international standardization and referencing.
  • C. TOR
    TOR is the standard three-letter abbreviation used to represent the Toronto Maple Leafs in sports standings, statistics, and media.
  • D. TH
    TH is the two-letter ISO 3166-1 alpha-2 country code assigned to Thailand for international standardization and identification.
  • E. TM
    TM is the New York Stock Exchange ticker symbol for Toyota Motor Corporation, the Japanese multinational automotive manufacturer.
  • 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_69a4948331fc8190b531ac9bec71c491 completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be0370b4819093618930f4eecfcc completed March 1, 2026, 10:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac831d216081909d36529fc4692361 completed March 7, 2026, 7:57 p.m.
NEDg Description generation batch_69ac83d4e7a08190bec19982db89a825 completed March 7, 2026, 8 p.m.
NED2 Entity disambiguation (via description) batch_69ac85ed4eb48190ab96ec575edd3b7c completed March 7, 2026, 8:09 p.m.
Created at: March 1, 2026, 7:46 p.m.