Triple

T1808855
Position Surface form Disambiguated ID Type / Status
Subject Este E40282 entity
Predicate ancientName P2834 FINISHED
Object Ateste
Ateste is the ancient name of the Italian town of Este, historically significant as a center of the Venetic civilization in northern Italy.
 E200705 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: Ateste | Statement: [Este, ancientName, Ateste]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ateste
Context triple: [Este, ancientName, Ateste]
  • A. Ato
    Ato is one of the futuristic, computer-generated "Spheriks" characters who served as an official mascot for the 2002 FIFA World Cup in South Korea and Japan.
  • B. Ate
    Ate is a populous district in the eastern part of Lima, Peru, known for its mix of industrial zones, residential areas, and growing commercial activity.
  • C. Aposticha
    Aposticha are a series of hymns with psalm verses chanted near the end of Orthodox Christian Vespers and other services, often highlighting the theme of the feast or liturgical day.
  • D. Ante
    Ante is a masculine given name of Croatian origin, commonly used in various South Slavic countries.
  • E. Antu
    Antu is one of the four 8.2-meter Unit Telescopes of the Very Large Telescope array operated by the European Southern Observatory at Paranal in Chile.
  • 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: Ateste
Triple: [Este, ancientName, Ateste]
Generated description
Ateste is the ancient name of the Italian town of Este, historically significant as a center of the Venetic civilization in northern Italy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ateste
Target entity description: Ateste is the ancient name of the Italian town of Este, historically significant as a center of the Venetic civilization in northern Italy.
  • A. Ato
    Ato is one of the futuristic, computer-generated "Spheriks" characters who served as an official mascot for the 2002 FIFA World Cup in South Korea and Japan.
  • B. Ate
    Ate is a populous district in the eastern part of Lima, Peru, known for its mix of industrial zones, residential areas, and growing commercial activity.
  • C. Aposticha
    Aposticha are a series of hymns with psalm verses chanted near the end of Orthodox Christian Vespers and other services, often highlighting the theme of the feast or liturgical day.
  • D. Ante
    Ante is a masculine given name of Croatian origin, commonly used in various South Slavic countries.
  • E. Antu
    Antu is one of the four 8.2-meter Unit Telescopes of the Very Large Telescope array operated by the European Southern Observatory at Paranal in Chile.
  • 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_69a88643a3388190a612f2ebe1fb29e7 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa65c310d88190bfd9c27fa238e648 completed March 6, 2026, 5:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69adb5e137bc81908294dd6b67789526 completed March 8, 2026, 5:46 p.m.
NEDg Description generation batch_69adb69d10188190b78bece656249ecd completed March 8, 2026, 5:49 p.m.
NED2 Entity disambiguation (via description) batch_69adb8c122e881908f0640edc5aaf305 completed March 8, 2026, 5:58 p.m.
Created at: March 4, 2026, 7:32 p.m.