Triple

T1889465
Position Surface form Disambiguated ID Type / Status
Subject GBAR experiment E41835 entity
Predicate usesFacility P105 FINISHED
Object ELENA
ELENA is a CERN accelerator ring designed to decelerate antiprotons to very low energies for precision antimatter experiments.
 E210177 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: ELENA | Statement: [GBAR experiment, usesFacility, ELENA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ELENA
Context triple: [GBAR experiment, usesFacility, ELENA]
  • A. Elena
    Elena is a feminine given name of Greek origin, commonly used in many languages as a variant of Helen or Helena.
  • B. Valeria
    Valeria is the clever, sharp-tongued heroine of George Farquhar’s Restoration comedy "The Witty Fair One."
  • C. Valeria
    Valeria was a Roman imperial princess and later empress, best known as the daughter of Emperor Diocletian and for her tragic fate during the political turmoil of the Tetrarchy.
  • D. Carmelina
    Carmelina is a lesser-known Broadway musical with music by Burton Lane and lyrics by Alan Jay Lerner, loosely based on the film "Buona Sera, Mrs. Campbell."
  • E. Cecilia
    Cecilia is a feminine given name of Latin origin, traditionally associated with Saint Cecilia, the patron saint of music.
  • 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: ELENA
Triple: [GBAR experiment, usesFacility, ELENA]
Generated description
ELENA is a CERN accelerator ring designed to decelerate antiprotons to very low energies for precision antimatter experiments.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ELENA
Target entity description: ELENA is a CERN accelerator ring designed to decelerate antiprotons to very low energies for precision antimatter experiments.
  • A. Elena
    Elena is a feminine given name of Greek origin, commonly used in many languages as a variant of Helen or Helena.
  • B. Valeria
    Valeria was a Roman imperial princess and later empress, best known as the daughter of Emperor Diocletian and for her tragic fate during the political turmoil of the Tetrarchy.
  • C. Valeria
    Valeria is the clever, sharp-tongued heroine of George Farquhar’s Restoration comedy "The Witty Fair One."
  • D. Carmelina
    Carmelina is a lesser-known Broadway musical with music by Burton Lane and lyrics by Alan Jay Lerner, loosely based on the film "Buona Sera, Mrs. Campbell."
  • E. Cecilia
    Cecilia is a feminine given name of Latin origin, traditionally associated with Saint Cecilia, the patron saint of music.
  • 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_69a8864b6de0819098d089f6a1b910a7 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb142e41881908fc7335673a9dec3 completed March 7, 2026, 5:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69addf665bd48190b08ff5159333b99b completed March 8, 2026, 8:43 p.m.
NEDg Description generation batch_69ade02321b881909e8bb087f6c3acd4 completed March 8, 2026, 8:46 p.m.
NED2 Entity disambiguation (via description) batch_69ade0d3f77481909cb4c9a57a9fb6a7 completed March 8, 2026, 8:49 p.m.
Created at: March 4, 2026, 7:34 p.m.