Triple

T3462455
Position Surface form Disambiguated ID Type / Status
Subject Campus Martius E73056 entity
Predicate partOf P40 FINISHED
Object Regio IX
Regio IX was one of the administrative regions of ancient Rome, encompassing the important public and religious area known as the Campus Martius.
 E358638 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: Regio IX | Statement: [Campus Martius, partOf, Regio IX]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Regio IX
Context triple: [Campus Martius, partOf, Regio IX]
  • A. Tokai
    Tokai is a suburb in Cape Town, South Africa, known for its residential areas, green spaces, and proximity to the Constantiaberg mountains.
  • B. Geita Region
    Geita Region is an administrative region in northwestern Tanzania, known for its significant gold mining activities and proximity to Lake Victoria.
  • C. Kaga no Kuni
    Kaga no Kuni was a historical province of Japan located in what is now southern Ishikawa Prefecture on the island of Honshu.
  • D. Taihoku
    Taihoku was the Japanese colonial-era name for Taipei, which served as the administrative and political center of Taiwan under Japanese rule.
  • E. Rhegion
    Rhegion was an important ancient Greek city located at the southern tip of Italy, strategically positioned on the Strait of Messina.
  • 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: Regio IX
Triple: [Campus Martius, partOf, Regio IX]
Generated description
Regio IX was one of the administrative regions of ancient Rome, encompassing the important public and religious area known as the Campus Martius.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Regio IX
Target entity description: Regio IX was one of the administrative regions of ancient Rome, encompassing the important public and religious area known as the Campus Martius.
  • A. Tokai
    Tokai is a suburb in Cape Town, South Africa, known for its residential areas, green spaces, and proximity to the Constantiaberg mountains.
  • B. Geita Region
    Geita Region is an administrative region in northwestern Tanzania, known for its significant gold mining activities and proximity to Lake Victoria.
  • C. Kaga no Kuni
    Kaga no Kuni was a historical province of Japan located in what is now southern Ishikawa Prefecture on the island of Honshu.
  • D. Taihoku
    Taihoku was the Japanese colonial-era name for Taipei, which served as the administrative and political center of Taiwan under Japanese rule.
  • E. Rhegion
    Rhegion was an important ancient Greek city located at the southern tip of Italy, strategically positioned on the Strait of Messina.
  • 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_69ad85b224d481908ff8be51338d24ff completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adbae867c4819091c76e63e44290b4 completed March 8, 2026, 6:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3612392308190b73dc2c757d02742 completed March 13, 2026, 12:58 a.m.
NEDg Description generation batch_69b362247e008190b0f708056b353f7b completed March 13, 2026, 1:02 a.m.
NED2 Entity disambiguation (via description) batch_69b362861bb48190a604de7bfdd6296d completed March 13, 2026, 1:04 a.m.
Created at: March 8, 2026, 3:17 p.m.