Triple

T12915473
Position Surface form Disambiguated ID Type / Status
Subject Federal Acquisition Regulation E308969 entity
Predicate abbreviation P43 FINISHED
Object FAR
FAR is the primary set of rules governing the acquisition process and procurement of goods and services by U.S. federal government agencies.
 E1008656 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: FAR | Statement: [Federal Acquisition Regulation, abbreviation, FAR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: FAR
Context triple: [Federal Acquisition Regulation, abbreviation, FAR]
  • A. FAR
    FAR is the acronym for Cuba’s national military organization, the Revolutionary Armed Forces.
  • B. FAR
    FAR is the commonly used abbreviation for the Intergovernmental Panel on Climate Change’s First Assessment Report, a foundational scientific evaluation of climate change published in 1990.
  • C. FAR
    FAR is the station code for Faro railway station, a key rail transport hub serving the city of Faro in southern Portugal’s Algarve region.
  • D. FAR
    FAR is the IATA airport code for Hector International Airport serving Fargo, North Dakota.
  • E. FAR
    FAR is a contemporary dance work by British choreographer Wayne McGregor, known for its innovative fusion of technology, complex movement vocabulary, and exploration of the relationship between the body and scientific ideas.
  • 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: FAR
Triple: [Federal Acquisition Regulation, abbreviation, FAR]
Generated description
FAR is the primary set of rules governing the acquisition process and procurement of goods and services by U.S. federal government agencies.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: FAR
Target entity description: FAR is the primary set of rules governing the acquisition process and procurement of goods and services by U.S. federal government agencies.
  • A. FAR
    FAR is the acronym for Morocco's Royal Armed Forces, the country's unified military organization responsible for national defense.
  • B. FAR
    FAR is the acronym for Cuba’s national military organization, the Revolutionary Armed Forces.
  • C. FAR
    FAR is the commonly used abbreviation for the Intergovernmental Panel on Climate Change’s First Assessment Report, a foundational scientific evaluation of climate change published in 1990.
  • D. FAR
    FAR is the IATA airport code for Hector International Airport serving Fargo, North Dakota.
  • E. FAR
    FAR is the station code for Faro railway station, a key rail transport hub serving the city of Faro in southern Portugal’s Algarve region.
  • 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_69d7bdf92b588190acdf2a2291ac4590 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d971a0d6508190bca9668e9e06abfe completed April 10, 2026, 9:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6a571a3e48190a32d362adc6eaee2 completed May 3, 2026, 1:31 a.m.
NEDg Description generation batch_69f6a66cd21081909283d70e0f5d06cb completed May 3, 2026, 1:35 a.m.
NED2 Entity disambiguation (via description) batch_69f6a7792f948190bb0b324bee0cd8ac completed May 3, 2026, 1:40 a.m.
Created at: April 9, 2026, 5:41 p.m.