Triple

T23332919
Position Surface form Disambiguated ID Type / Status
Subject Data Retention and Investigatory Powers Act 2014 E591494 entity
Predicate shortName P43 FINISHED
Object DRIPA
DRIPA is a UK law enacted in 2014 that expanded government powers to retain communications data and conduct surveillance for investigatory purposes.
 E1579691 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: DRIPA | Statement: [Data Retention and Investigatory Powers Act 2014, shortName, DRIPA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DRIPA
Context triple: [Data Retention and Investigatory Powers Act 2014, shortName, DRIPA]
  • A. DRA
    DRA is the commonly used abbreviation for the Democratic Republic of Afghanistan, the Soviet-aligned Afghan state that existed from 1978 to 1992.
  • B. DRS
    DRS is the three-letter IATA airport code for Dresden Airport in Dresden, Germany.
  • C. DRS
    DRS is the official abbreviation for the Roman Catholic Diocese of Rottenburg-Stuttgart in Germany.
  • D. DRS
    DRS is the stock ticker symbol for Leonardo DRS, an American defense technology company specializing in advanced military and intelligence systems.
  • E. DURIP
    DURIP is a U.S. Department of Defense funding program that provides universities with advanced research instrumentation to support cutting-edge defense-related science and engineering.
  • 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: DRIPA
Triple: [Data Retention and Investigatory Powers Act 2014, shortName, DRIPA]
Generated description
DRIPA is a UK law enacted in 2014 that expanded government powers to retain communications data and conduct surveillance for investigatory purposes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DRIPA
Target entity description: DRIPA is a UK law enacted in 2014 that expanded government powers to retain communications data and conduct surveillance for investigatory purposes.
  • A. DRA
    DRA is the commonly used abbreviation for the Democratic Republic of Afghanistan, the Soviet-aligned Afghan state that existed from 1978 to 1992.
  • B. DRS
    DRS is the three-letter IATA airport code for Dresden Airport in Dresden, Germany.
  • C. DRS
    DRS is the official abbreviation for the Roman Catholic Diocese of Rottenburg-Stuttgart in Germany.
  • D. DRS
    DRS is the stock ticker symbol for Leonardo DRS, an American defense technology company specializing in advanced military and intelligence systems.
  • E. DURIP
    DURIP is a U.S. Department of Defense funding program that provides universities with advanced research instrumentation to support cutting-edge defense-related science and engineering.
  • 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_69e25d20156c81908c5c53195bd9c738 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f197eecc5c81908089eb43bc701196 completed April 29, 2026, 5:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c4cb082f881909256738232b060b9 completed May 19, 2026, 11:42 a.m.
NEDg Description generation batch_6a0c4e669b6481909f198d1c51b68bf3 completed May 19, 2026, 11:49 a.m.
NED2 Entity disambiguation (via description) batch_6a0c4f011a188190b801f2ae0f134356 completed May 19, 2026, 11:52 a.m.
Created at: April 17, 2026, 5:15 p.m.