Triple

T494721
Position Surface form Disambiguated ID Type / Status
Subject St Martin E10266 entity
Predicate associatedWith P37 FINISHED
Object Gaul E24814 NE FINISHED

How this triple was built (2 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: Gaul | Statement: [St Martin, associatedWith, Gaul]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gaul
Context triple: [St Martin, associatedWith, Gaul]
  • A. Gaul chosen
    Gaul was a large region of Western Europe in antiquity, encompassing much of present-day France and neighboring areas, inhabited primarily by Celtic tribes before Roman conquest.
  • B. Raetia
    Raetia was a frontier province of the Roman Empire in the central Alps region, covering parts of modern Switzerland, Germany, Austria, and Italy.
  • C. Brittany
    Brittany is a historic cultural region in northwest France known for its distinct Celtic heritage, Breton language, rugged coastline, and strong Catholic traditions.
  • D. Pannonia
    Pannonia was an ancient Roman province in Central Europe, roughly corresponding to parts of modern Hungary and neighboring countries, that served as a key frontier region of the empire.
  • E. Gaulish
    Gaulish was an ancient Celtic language once spoken in much of Western and Central Europe, particularly in the region corresponding to modern-day France and surrounding areas.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a2e847df8481909239ec08ccf1e376 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f0fdd5608190815fa36485df8962 completed Feb. 28, 2026, 1:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69a47d2da4488190be3146538a4f3d46 completed March 1, 2026, 5:53 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.