Triple

T2734111
Position Surface form Disambiguated ID Type / Status
Subject Orléans E60387 entity
Predicate historicalName P65 FINISHED
Object Aurelianum
Aurelianum is the ancient Latin name for the French city of Orléans, reflecting its origins as a Roman settlement.
E291982 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: Aurelianum | Statement: [Orléans, historicalName, Aurelianum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aurelianum
Context triple: [Orléans, historicalName, Aurelianum]
  • A. Durostorum
    Durostorum was a major Roman military and urban center on the lower Danube, located in the province of Moesia (modern Silistra, Bulgaria).
  • B. Aquincum
    Aquincum was an important ancient Roman military and civilian settlement located in what is now northern Budapest, Hungary.
  • C. Flavia Neapolis
    Flavia Neapolis was a Roman city in Samaria, founded in the 1st century CE near ancient Shechem and known today as Nablus in the West Bank.
  • D. Marciana
    Marciana is a historic hilltop village on the Italian island of Elba, known for its medieval architecture and scenic views over the Tyrrhenian Sea.
  • E. Carnuntum
    Carnuntum was a major Roman military camp and later a significant provincial capital and trading city on the Danube frontier in what is now eastern Austria.
  • 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: Aurelianum
Triple: [Orléans, historicalName, Aurelianum]
Generated description
Aurelianum is the ancient Latin name for the French city of Orléans, reflecting its origins as a Roman settlement.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Aurelianum
Target entity description: Aurelianum is the ancient Latin name for the French city of Orléans, reflecting its origins as a Roman settlement.
  • A. Durostorum
    Durostorum was a major Roman military and urban center on the lower Danube, located in the province of Moesia (modern Silistra, Bulgaria).
  • B. Aquincum
    Aquincum was an important ancient Roman military and civilian settlement located in what is now northern Budapest, Hungary.
  • C. Flavia Neapolis
    Flavia Neapolis was a Roman city in Samaria, founded in the 1st century CE near ancient Shechem and known today as Nablus in the West Bank.
  • D. Marciana
    Marciana is a historic hilltop village on the Italian island of Elba, known for its medieval architecture and scenic views over the Tyrrhenian Sea.
  • E. Carnuntum
    Carnuntum was a major Roman military camp and later a significant provincial capital and trading city on the Danube frontier in what is now eastern Austria.
  • 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_69ab4b75cd908190b691ef0d1801acda completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdb0e7b888190bfa5d2e33f00ec0f completed March 7, 2026, 8 a.m.
NED1 Entity disambiguation (via context triple) batch_69afb6a15e548190a118880f9904f9cc completed March 10, 2026, 6:13 a.m.
NEDg Description generation batch_69afb78d9f0c8190ad276922aa19945d completed March 10, 2026, 6:17 a.m.
NED2 Entity disambiguation (via description) batch_69afb7e8a8548190b5b4e7772e0adcf6 completed March 10, 2026, 6:19 a.m.
Created at: March 6, 2026, 9:56 p.m.