Triple

T189571
Position Surface form Disambiguated ID Type / Status
Subject Division of Nuclear Physics E3688 entity
Predicate abbreviation P43 FINISHED
Object DNP
DNP is the commonly used abbreviation for the Division of Nuclear Physics, a professional organization focused on research and advancement in nuclear physics.
 E24001 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: DNP | Statement: [Division of Nuclear Physics, abbreviation, DNP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DNP
Context triple: [Division of Nuclear Physics, abbreviation, DNP]
  • A. DNB
    DNB is the standard abbreviation for the Dictionary of National Biography, a major reference work containing biographical articles on notable figures from British history.
  • B. DNI
    DNI is the commonly used acronym for the Director of National Intelligence, the head of the U.S. intelligence community.
  • C. DNVA
    DNVA is the abbreviation for the Norwegian Academy of Science and Letters, a prestigious scholarly society that promotes scientific and scholarly research in Norway.
  • D. MNP
    MNP is the three-letter ISO 3166-1 alpha-3 country code assigned to the Northern Mariana Islands.
  • E. Nurse
    Nurse is a common English occupational surname originally referring to someone who worked as a caregiver or medical attendant.
  • 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: DNP
Triple: [Division of Nuclear Physics, abbreviation, DNP]
Generated description
DNP is the commonly used abbreviation for the Division of Nuclear Physics, a professional organization focused on research and advancement in nuclear physics.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DNP
Target entity description: DNP is the commonly used abbreviation for the Division of Nuclear Physics, a professional organization focused on research and advancement in nuclear physics.
  • A. DNB
    DNB is the standard abbreviation for the Dictionary of National Biography, a major reference work containing biographical articles on notable figures from British history.
  • B. DNI
    DNI is the commonly used acronym for the Director of National Intelligence, the head of the U.S. intelligence community.
  • C. DNVA
    DNVA is the abbreviation for the Norwegian Academy of Science and Letters, a prestigious scholarly society that promotes scientific and scholarly research in Norway.
  • D. MNP
    MNP is the three-letter ISO 3166-1 alpha-3 country code assigned to the Northern Mariana Islands.
  • E. Nurse
    Nurse is a common English occupational surname originally referring to someone who worked as a caregiver or medical attendant.
  • 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_69a2548debd48190ae3a06d6e65b53c6 completed Feb. 28, 2026, 2:35 a.m.
NER Named-entity recognition batch_69a2594c385481909e1e088e45c460a4 completed Feb. 28, 2026, 2:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69a305e511a08190a560125ed3839a0c completed Feb. 28, 2026, 3:12 p.m.
NEDg Description generation batch_69a30679b0648190975dcfaf4f9846bf completed Feb. 28, 2026, 3:15 p.m.
NED2 Entity disambiguation (via description) batch_69a306e6ce6c8190a77d42643914b03a completed Feb. 28, 2026, 3:16 p.m.
Created at: Feb. 28, 2026, 2:41 a.m.