Triple

T3616109
Position Surface form Disambiguated ID Type / Status
Subject NuMI beamline E76603 entity
Predicate servesExperiment P1591 FINISHED
Object ArgoNeuT
ArgoNeuT is a liquid argon time projection chamber neutrino detector used to study neutrino interactions in a high-intensity accelerator beam.
 E373837 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: ArgoNeuT | Statement: [NuMI beamline, servesExperiment, ArgoNeuT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ArgoNeuT
Context triple: [NuMI beamline, servesExperiment, ArgoNeuT]
  • A. ARO
    ARO is the U.S. Army Research Office, a primary Army organization that funds and manages basic scientific research to support future military technologies and capabilities.
  • B. Agnontas
    Agnontas is a small coastal village and port on the Greek island of Skopelos, known for its scenic bay and seaside tavernas.
  • C. Afiartis
    Afiartis is a coastal area on the Greek island of Karpathos known for its beaches and strong winds that make it popular for windsurfing and other water sports.
  • D. Nafe
    Nafe is an indigenous Oceanic language spoken in Vanuatu.
  • E. Ateso
    Ateso is a Nilotic language spoken primarily by the Teso people of eastern Uganda and western Kenya.
  • 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: ArgoNeuT
Triple: [NuMI beamline, servesExperiment, ArgoNeuT]
Generated description
ArgoNeuT is a liquid argon time projection chamber neutrino detector used to study neutrino interactions in a high-intensity accelerator beam.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ArgoNeuT
Target entity description: ArgoNeuT is a liquid argon time projection chamber neutrino detector used to study neutrino interactions in a high-intensity accelerator beam.
  • A. ARO
    ARO is the U.S. Army Research Office, a primary Army organization that funds and manages basic scientific research to support future military technologies and capabilities.
  • B. Agnontas
    Agnontas is a small coastal village and port on the Greek island of Skopelos, known for its scenic bay and seaside tavernas.
  • C. Afiartis
    Afiartis is a coastal area on the Greek island of Karpathos known for its beaches and strong winds that make it popular for windsurfing and other water sports.
  • D. Nafe
    Nafe is an indigenous Oceanic language spoken in Vanuatu.
  • E. Ateso
    Ateso is a Nilotic language spoken primarily by the Teso people of eastern Uganda and western Kenya.
  • 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_69ad85dae2fc81908d1ceadbc6af0089 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc27c98088190a493c9eddf6b206a completed March 8, 2026, 6:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4331a82688190add137b1f68c955e completed March 13, 2026, 3:54 p.m.
NEDg Description generation batch_69b438135e8c81909c56e1c04499268b completed March 13, 2026, 4:15 p.m.
NED2 Entity disambiguation (via description) batch_69b4388a1ecc81908e1de9f8bcfc008d completed March 13, 2026, 4:17 p.m.
Created at: March 8, 2026, 3:23 p.m.