Triple

T8832343
Position Surface form Disambiguated ID Type / Status
Subject BASE E210174 entity
Predicate relatedExperiment P37 FINISHED
Object ATRAP
ATRAP is a CERN-based physics experiment focused on producing, trapping, and precisely studying antihydrogen atoms to test fundamental symmetries between matter and antimatter.
 E761920 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: ATRAP | Statement: [BASE, relatedExperiment, ATRAP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ATRAP
Context triple: [BASE, relatedExperiment, ATRAP]
  • A. ALTR
    ALTR is the stock ticker symbol for Altera Corporation, a former leading manufacturer of programmable logic devices that was acquired by Intel.
  • B. Atripé
    Atripé was an ancient Egyptian town in Upper Egypt notable as the home of the influential Coptic monastic leader Shenoute.
  • C. Atreseries
    Atreseries is a Spanish television channel owned by Atresmedia that specializes in broadcasting TV series and fiction content.
  • D. Ate
    Ate is a populous district in the eastern part of Lima, Peru, known for its mix of industrial zones, residential areas, and growing commercial activity.
  • E. Ate
    Ate is the Greek goddess of ruin, folly, and delusion, known for leading gods and mortals alike into reckless actions and disastrous consequences.
  • 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: ATRAP
Triple: [BASE, relatedExperiment, ATRAP]
Generated description
ATRAP is a CERN-based physics experiment focused on producing, trapping, and precisely studying antihydrogen atoms to test fundamental symmetries between matter and antimatter.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ATRAP
Target entity description: ATRAP is a CERN-based physics experiment focused on producing, trapping, and precisely studying antihydrogen atoms to test fundamental symmetries between matter and antimatter.
  • A. ALTR
    ALTR is the stock ticker symbol for Altera Corporation, a former leading manufacturer of programmable logic devices that was acquired by Intel.
  • B. Atripé
    Atripé was an ancient Egyptian town in Upper Egypt notable as the home of the influential Coptic monastic leader Shenoute.
  • C. Atreseries
    Atreseries is a Spanish television channel owned by Atresmedia that specializes in broadcasting TV series and fiction content.
  • D. Ate
    Ate is a populous district in the eastern part of Lima, Peru, known for its mix of industrial zones, residential areas, and growing commercial activity.
  • E. Ate
    Ate is the Greek goddess of ruin, folly, and delusion, known for leading gods and mortals alike into reckless actions and disastrous consequences.
  • 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_69ca8388549c819095fd94eadefbb007 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc605005788190a4df1fe317f3056a completed April 1, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69cf896cf5a8819098a76288bd505c1e completed April 3, 2026, 9:33 a.m.
NEDg Description generation batch_69cf8adfe8a08190a959f650207a2ca8 completed April 3, 2026, 9:39 a.m.
NED2 Entity disambiguation (via description) batch_69cf8bc521dc81908918b48a25f290bb completed April 3, 2026, 9:43 a.m.
Created at: March 30, 2026, 6:47 p.m.