Triple

T1166738
Position Surface form Disambiguated ID Type / Status
Subject Gaul E24814 entity
Predicate majorCity P316 FINISHED
Object Burdigala
Burdigala was the ancient Roman-era city in Gaul that later became modern-day Bordeaux, an important commercial and cultural center.
 E135117 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: Burdigala | Statement: [Gaul, majorCity, Burdigala]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Burdigala
Context triple: [Gaul, majorCity, Burdigala]
  • A. Zancle
    Zancle was an ancient Greek city in Sicily, known later as Messana (modern Messina), and was one of the key colonies of Magna Graecia.
  • B. Massilia
    Massilia was the ancient Greek colony and major Mediterranean trading port that later became the modern French city of Marseille.
  • C. Populonia
    Populonia was an important ancient coastal city of Etruria, known for its maritime trade, metalworking, and strategic position on the Tyrrhenian Sea.
  • D. Thugga
    Thugga is an ancient Roman-Berber city in modern-day Tunisia renowned for its well-preserved ruins and status as a UNESCO World Heritage Site.
  • E. Tarquinia
    Tarquinia is an ancient Etruscan city in central Italy renowned for its richly painted tombs and significant archaeological remains.
  • 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: Burdigala
Triple: [Gaul, majorCity, Burdigala]
Generated description
Burdigala was the ancient Roman-era city in Gaul that later became modern-day Bordeaux, an important commercial and cultural center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Burdigala
Target entity description: Burdigala was the ancient Roman-era city in Gaul that later became modern-day Bordeaux, an important commercial and cultural center.
  • A. Zancle
    Zancle was an ancient Greek city in Sicily, known later as Messana (modern Messina), and was one of the key colonies of Magna Graecia.
  • B. Massilia
    Massilia was the ancient Greek colony and major Mediterranean trading port that later became the modern French city of Marseille.
  • C. Populonia
    Populonia was an important ancient coastal city of Etruria, known for its maritime trade, metalworking, and strategic position on the Tyrrhenian Sea.
  • D. Thugga
    Thugga is an ancient Roman-Berber city in modern-day Tunisia renowned for its well-preserved ruins and status as a UNESCO World Heritage Site.
  • E. Tarquinia
    Tarquinia is an ancient Etruscan city in central Italy renowned for its richly painted tombs and significant archaeological remains.
  • 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_69a494082a7c819095004f423f294a64 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bccd75048190b8ce88237c1a748b completed March 1, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac6f17aa608190920b7df62b8dd903 completed March 7, 2026, 6:31 p.m.
NEDg Description generation batch_69ac6fc5442c8190a5d824881f05d468 completed March 7, 2026, 6:34 p.m.
NED2 Entity disambiguation (via description) batch_69ac7026dda48190a72f671dba9ac17b completed March 7, 2026, 6:36 p.m.
Created at: March 1, 2026, 7:45 p.m.