Triple

T7902792
Position Surface form Disambiguated ID Type / Status
Subject English Partnerships E183495 entity
Predicate alsoKnownAs P39 FINISHED
Object EP
EP is the commonly used abbreviation for English Partnerships, the former national regeneration agency for England responsible for land development and urban renewal projects.
 E700564 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: EP | Statement: [English Partnerships, alsoKnownAs, EP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: EP
Context triple: [English Partnerships, alsoKnownAs, EP]
  • A. EP
    The EP is the directly elected legislative body of the European Union that works with other EU institutions to pass laws and oversee policies across member states.
  • B. PE
    PE is a postcode area in eastern England covering parts of Cambridgeshire, Lincolnshire, Norfolk, and surrounding counties.
  • C. PE
    PE is the two-letter ISO 3166-1 alpha-2 country code assigned to Peru for international standardization and referencing.
  • D. PE
    PE is the official two-letter postal abbreviation used for Prince Edward Island, a Canadian province.
  • E. PE
    PE is the official vehicle registration code for the Brazilian state of Pernambuco.
  • 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: EP
Triple: [English Partnerships, alsoKnownAs, EP]
Generated description
EP is the commonly used abbreviation for English Partnerships, the former national regeneration agency for England responsible for land development and urban renewal projects.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: EP
Target entity description: EP is the commonly used abbreviation for English Partnerships, the former national regeneration agency for England responsible for land development and urban renewal projects.
  • A. EP
    The EP is the directly elected legislative body of the European Union that works with other EU institutions to pass laws and oversee policies across member states.
  • B. PE
    PE is a postcode area in eastern England covering parts of Cambridgeshire, Lincolnshire, Norfolk, and surrounding counties.
  • C. PE
    PE is the two-letter ISO 3166-1 alpha-2 country code assigned to Peru for international standardization and referencing.
  • D. PE
    PE is the official two-letter postal abbreviation used for Prince Edward Island, a Canadian province.
  • E. PE
    PE is the official vehicle registration code for the Brazilian state of Pernambuco.
  • 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_69ca828d13088190b222be7aa9f9315c completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3a41b0fc81909890f2e4f432a5cf completed March 31, 2026, 3:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5bc35cec8190bda3dfe7d8d4ed18 completed March 31, 2026, 5:29 a.m.
NEDg Description generation batch_69cb7632cbbc819087107c8d2172a038 completed March 31, 2026, 7:22 a.m.
NED2 Entity disambiguation (via description) batch_69cbb64eee408190a66cbd0cba3054b4 completed March 31, 2026, 11:55 a.m.
Created at: March 30, 2026, 5:02 p.m.