Triple

T3803198
Position Surface form Disambiguated ID Type / Status
Subject Antoninus Pius E91738 entity
Predicate deathPlace P21 FINISHED
Object Lorium
Lorium was an ancient Roman settlement along the Via Aurelia in Etruria, known as an imperial villa site associated with Emperor Antoninus Pius.
E387625 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: Lorium | Statement: [Antoninus Pius, deathPlace, Lorium]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lorium
Context triple: [Antoninus Pius, deathPlace, Lorium]
  • A. Pearre
    Pearre is a given name used as the middle name of U.S. Air Force General Charles Pearre Cabell.
  • B. Thaton
    Thaton is an ancient city in southern Myanmar historically significant as a major center of the Mon kingdom and Theravada Buddhism in the region.
  • C. Livermore
    Livermore is a city in California’s Tri-Valley region known for its wine country, historic downtown, and proximity to major scientific research facilities.
  • D. Avallon
    Avallon is a historic commune in central France known for its medieval architecture and scenic location on a granite outcrop in the Burgundy region.
  • E. Edenborn
    Edenborn is a science fiction novel by Nick Sagan that continues his post-apocalyptic series exploring genetic engineering and the future of humanity.
  • 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: Lorium
Triple: [Antoninus Pius, deathPlace, Lorium]
Generated description
Lorium was an ancient Roman settlement along the Via Aurelia in Etruria, known as an imperial villa site associated with Emperor Antoninus Pius.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lorium
Target entity description: Lorium was an ancient Roman settlement along the Via Aurelia in Etruria, known as an imperial villa site associated with Emperor Antoninus Pius.
  • A. Pearre
    Pearre is a given name used as the middle name of U.S. Air Force General Charles Pearre Cabell.
  • B. Thaton
    Thaton is an ancient city in southern Myanmar historically significant as a major center of the Mon kingdom and Theravada Buddhism in the region.
  • C. Livermore
    Livermore is a city in California’s Tri-Valley region known for its wine country, historic downtown, and proximity to major scientific research facilities.
  • D. Avallon
    Avallon is a historic commune in central France known for its medieval architecture and scenic location on a granite outcrop in the Burgundy region.
  • E. Edenborn
    Edenborn is a science fiction novel by Nick Sagan that continues his post-apocalyptic series exploring genetic engineering and the future of humanity.
  • 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_69aed96354f48190a768966d6bd19b04 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aee7bacf2881908198a77063d15d16 completed March 9, 2026, 3:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4f06889c88190ab4d8da7f0dfeadd completed March 14, 2026, 5:21 a.m.
NEDg Description generation batch_69b4f0e77efc8190b4459d4559261a2f completed March 14, 2026, 5:23 a.m.
NED2 Entity disambiguation (via description) batch_69b4f15cfde88190bcb2680b90f98111 completed March 14, 2026, 5:25 a.m.
Created at: March 9, 2026, 3:15 p.m.