Triple

T4199873
Position Surface form Disambiguated ID Type / Status
Subject Umbrians E86039 entity
Predicate majorSite P2462 FINISHED
Object Ameria
Ameria is an ancient Umbrian town in central Italy, known today as Amelia, with significant archaeological and historical remains from pre-Roman and Roman times.
 E419009 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: Ameria | Statement: [Umbrians, majorSite, Ameria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ameria
Context triple: [Umbrians, majorSite, Ameria]
  • A. Amery
    Amery is an English surname most notably associated with a British political family, including Conservative politician Julian Amery.
  • B. Amer
    Amer is a common Arabic surname borne by various notable individuals across the Middle East and North Africa.
  • C. Euramerica
    Euramerica was an ancient Paleozoic-era supercontinent formed by the collision of Laurentia, Baltica, and Avalonia, which later contributed to the assembly of Pangaea.
  • D. Amerika
    Amerika is a novel by Franz Kafka that follows a young European immigrant’s surreal and often absurd experiences in the United States.
  • E. América
    América is a popular Mexican professional football club based in Mexico City, widely recognized as one of the most successful and supported teams in Liga MX.
  • 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: Ameria
Triple: [Umbrians, majorSite, Ameria]
Generated description
Ameria is an ancient Umbrian town in central Italy, known today as Amelia, with significant archaeological and historical remains from pre-Roman and Roman times.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ameria
Target entity description: Ameria is an ancient Umbrian town in central Italy, known today as Amelia, with significant archaeological and historical remains from pre-Roman and Roman times.
  • A. Amery
    Amery is an English surname most notably associated with a British political family, including Conservative politician Julian Amery.
  • B. Amer
    Amer is a common Arabic surname borne by various notable individuals across the Middle East and North Africa.
  • C. Euramerica
    Euramerica was an ancient Paleozoic-era supercontinent formed by the collision of Laurentia, Baltica, and Avalonia, which later contributed to the assembly of Pangaea.
  • D. Amerika
    Amerika is a novel by Franz Kafka that follows a young European immigrant’s surreal and often absurd experiences in the United States.
  • E. América
    América is a popular Mexican professional football club based in Mexico City, widely recognized as one of the most successful and supported teams in Liga MX.
  • 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_69aed93b89f48190a31f6d57c760e42f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af0363bbb8819093f396afe91972e2 completed March 9, 2026, 5:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69b58a14eda88190aaca14644c3e041a completed March 14, 2026, 4:17 p.m.
NEDg Description generation batch_69b58ae74ef481908a21ab5f649750e3 completed March 14, 2026, 4:20 p.m.
NED2 Entity disambiguation (via description) batch_69b58b7aad248190ac4f25fb424e9217 completed March 14, 2026, 4:23 p.m.
Created at: March 9, 2026, 3:49 p.m.