Triple

T1166331
Position Surface form Disambiguated ID Type / Status
Subject North Area of CERN SPS E24806 entity
Predicate servesExperiment P1591 FINISHED
Object AMBER
AMBER is a fixed-target experiment at CERN designed to study hadron structure and strong interaction dynamics using high-energy secondary and tertiary beams from the SPS.
 E134374 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: AMBER | Statement: [North Area of CERN SPS, servesExperiment, AMBER]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: AMBER
Context triple: [North Area of CERN SPS, servesExperiment, AMBER]
  • A. Amber
    Amber is a character from the film "Green Room," a tense horror-thriller about a punk band trapped in a remote venue controlled by violent neo-Nazis.
  • B. Annabella
    Annabella was a French film actress of the 1930s and 1940s, known for her work in both European and Hollywood cinema.
  • C. Amanda
    Amanda is the central character of the work "The Relapse," around whom the main events and conflicts of the story revolve.
  • D. Abemama
    Abemama is a central Pacific atoll in the island nation of Kiribati, known for its lagoon, traditional villages, and role in the country’s colonial and wartime history.
  • E. Amalia
    Amalia is the Dutch crown princess, heir apparent to the throne of the Kingdom of the Netherlands.
  • 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: AMBER
Triple: [North Area of CERN SPS, servesExperiment, AMBER]
Generated description
AMBER is a fixed-target experiment at CERN designed to study hadron structure and strong interaction dynamics using high-energy secondary and tertiary beams from the SPS.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: AMBER
Target entity description: AMBER is a fixed-target experiment at CERN designed to study hadron structure and strong interaction dynamics using high-energy secondary and tertiary beams from the SPS.
  • A. Amber
    Amber is a character from the film "Green Room," a tense horror-thriller about a punk band trapped in a remote venue controlled by violent neo-Nazis.
  • B. Annabella
    Annabella was a French film actress of the 1930s and 1940s, known for her work in both European and Hollywood cinema.
  • C. Amanda
    Amanda is the central character of the work "The Relapse," around whom the main events and conflicts of the story revolve.
  • D. Abemama
    Abemama is a central Pacific atoll in the island nation of Kiribati, known for its lagoon, traditional villages, and role in the country’s colonial and wartime history.
  • E. Amalia
    Amalia is the Dutch crown princess, heir apparent to the throne of the Kingdom of the Netherlands.
  • 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_69a494082a7c819095004f423f294a64 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bccc62a88190882d8801908015a4 completed March 1, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac668290008190a5e175c0a2e5feb0 completed March 7, 2026, 5:55 p.m.
NEDg Description generation batch_69ac6aaa84fc81908130543b14938e41 completed March 7, 2026, 6:12 p.m.
NED2 Entity disambiguation (via description) batch_69ac6b24987c819080e00b49df8f6edb completed March 7, 2026, 6:15 p.m.
Created at: March 1, 2026, 7:45 p.m.