Triple

T16284350
Position Surface form Disambiguated ID Type / Status
Subject Directorate of Plans E395349 entity
Predicate officialAbbreviation P3776 FINISHED
Object DDP E1204475 NE FINISHED

How this triple was built (2 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: DDP | Statement: [Directorate of Plans, officialAbbreviation, DDP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DDP
Context triple: [Directorate of Plans, officialAbbreviation, DDP]
  • A. DDP
    DDP is a network protocol used in AppleTalk for connectionless, best-effort delivery of datagram packets between devices.
  • B. DDP chosen
    DDP was the former name of the CIA’s clandestine operations branch, responsible for covert action and espionage during much of the Cold War.
  • C. DDP
    DDP was a liberal political party in the Weimar Republic that advocated democratic reforms, civil liberties, and a parliamentary system in post–World War I Germany.
  • D. DPP
    DPP is the Maryland state agency responsible for supervising individuals on parole and probation and supporting their reintegration into the community.
  • E. DPP
    DPP is the main public transport operator in Prague, responsible for running the city’s metro, trams, and buses.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d87f22c7248190a54c949738441e2e completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e24912c5808190a0d9c9f491315068 completed April 17, 2026, 2:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a001f93240881909d0beaddc92f0ad5 completed May 10, 2026, 6:02 a.m.
Created at: April 10, 2026, 5:05 a.m.