Triple

T3763632
Position Surface form Disambiguated ID Type / Status
Subject Biological and Environmental Research program E82619 entity
Predicate shortName P43 FINISHED
Object BER
BER is a U.S. Department of Energy research program that advances fundamental science on biological systems and environmental processes to address energy and climate challenges.
 E386201 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: BER | Statement: [Biological and Environmental Research program, shortName, BER]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BER
Context triple: [Biological and Environmental Research program, shortName, BER]
  • A. BER
    BER is Berlin Brandenburg Airport, the main international airport serving Germany’s capital region.
  • B. BER
    BER is the ICAO airline designator formerly used by the now-defunct German carrier Air Berlin.
  • C. BEL
    BEL is the ICAO airline designator used to identify Brussels Airlines in international aviation operations.
  • D. BEL
    BEL is the three-letter ISO 3166-1 alpha-3 country code that uniquely identifies Belgium in international standards and data systems.
  • E. BUR
    BUR is the three-letter IATA airport code for Hollywood Burbank Airport, a commercial airport serving the Los Angeles area in Southern California.
  • 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: BER
Triple: [Biological and Environmental Research program, shortName, BER]
Generated description
BER is a U.S. Department of Energy research program that advances fundamental science on biological systems and environmental processes to address energy and climate challenges.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BER
Target entity description: BER is a U.S. Department of Energy research program that advances fundamental science on biological systems and environmental processes to address energy and climate challenges.
  • A. BER
    BER is Berlin Brandenburg Airport, the main international airport serving Germany’s capital region.
  • B. BER
    BER is the ICAO airline designator formerly used by the now-defunct German carrier Air Berlin.
  • C. BEL
    BEL is the ICAO airline designator used to identify Brussels Airlines in international aviation operations.
  • D. BEL
    BEL is the three-letter ISO 3166-1 alpha-3 country code that uniquely identifies Belgium in international standards and data systems.
  • E. BUR
    BUR is the three-letter IATA airport code for Hollywood Burbank Airport, a commercial airport serving the Los Angeles area in Southern California.
  • 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_69ad8b207b0081909d2b48843fbd8795 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcbfbecf8819099d80af480cbe2d2 completed March 8, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4e51e54108190ab60e189cfbb0db0 completed March 14, 2026, 4:33 a.m.
NEDg Description generation batch_69b4e6a49ffc81908d6322b1ca6f6327 completed March 14, 2026, 4:40 a.m.
NED2 Entity disambiguation (via description) batch_69b4e7311cc4819098926b36b94cae96 completed March 14, 2026, 4:42 a.m.
Created at: March 8, 2026, 3:35 p.m.