Triple

T8131727
Position Surface form Disambiguated ID Type / Status
Subject Picatinny Arsenal E189866 entity
Predicate hasAbbreviation P43 FINISHED
Object PICA
PICA is the abbreviation for Picatinny Arsenal, a U.S. Army research and manufacturing facility specializing in armaments and munitions development.
E713985 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: PICA | Statement: [Picatinny Arsenal, hasAbbreviation, PICA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PICA
Context triple: [Picatinny Arsenal, hasAbbreviation, PICA]
  • A. PICA-X
    PICA-X is a SpaceX-developed, advanced heat shield material designed to protect Dragon spacecraft during the intense heat of atmospheric reentry.
  • B. Pikiell
    Pikiell is the surname of Steve Pikiell, an American college basketball coach best known for leading the Rutgers Scarlet Knights men's basketball program.
  • C. PIK
    PIK is a leading German research institute focused on analyzing the causes and impacts of climate change and developing strategies for sustainable solutions.
  • D. PIK
    PIK is the three-letter IATA airport code for Glasgow Prestwick Airport in South Ayrshire, Scotland.
  • E. PICA format
    PICA format is a library data exchange and cataloging standard widely used in German-speaking countries, particularly in academic and research libraries.
  • 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: PICA
Triple: [Picatinny Arsenal, hasAbbreviation, PICA]
Generated description
PICA is the abbreviation for Picatinny Arsenal, a U.S. Army research and manufacturing facility specializing in armaments and munitions development.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: PICA
Target entity description: PICA is the abbreviation for Picatinny Arsenal, a U.S. Army research and manufacturing facility specializing in armaments and munitions development.
  • A. PICA-X
    PICA-X is a SpaceX-developed, advanced heat shield material designed to protect Dragon spacecraft during the intense heat of atmospheric reentry.
  • B. Pikiell
    Pikiell is the surname of Steve Pikiell, an American college basketball coach best known for leading the Rutgers Scarlet Knights men's basketball program.
  • C. PIK
    PIK is a leading German research institute focused on analyzing the causes and impacts of climate change and developing strategies for sustainable solutions.
  • D. PIK
    PIK is the three-letter IATA airport code for Glasgow Prestwick Airport in South Ayrshire, Scotland.
  • E. PICA format
    PICA format is a library data exchange and cataloging standard widely used in German-speaking countries, particularly in academic and research libraries.
  • 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_69ca82bcb4848190a9a9d036ad768642 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb43b96cd481908c0679050c35d83f completed March 31, 2026, 3:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc9482113881909439c9e43fbc933f completed April 1, 2026, 3:44 a.m.
NEDg Description generation batch_69cc95c0b19881908521cce5ac0fe197 completed April 1, 2026, 3:49 a.m.
NED2 Entity disambiguation (via description) batch_69cc970698f88190a0869515904e50e3 completed April 1, 2026, 3:54 a.m.
Created at: March 30, 2026, 5:34 p.m.