Triple

T5360686
Position Surface form Disambiguated ID Type / Status
Subject Gustave Crauck E103011 entity
Predicate workLocation P7 FINISHED
Object Valenciennes E112910 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: Valenciennes | Statement: [Gustave Crauck, workLocation, Valenciennes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valenciennes
Context triple: [Gustave Crauck, workLocation, Valenciennes]
  • A. Valenciennes chosen
    Valenciennes is a historic industrial city in northern France near the Belgian border, known for its former coal and steel industries and its rich artistic and architectural heritage.
  • B. Villeneuve d’Ascq
    Villeneuve d’Ascq is a suburban city in northern France near Lille, known for its universities, technology parks, and modernist urban planning.
  • C. Saint-Omer
    Saint-Omer is a historic town in northern France known for its medieval architecture, strategic military importance, and role in Franco-Spanish conflicts.
  • D. Houilles
    Houilles is a suburban commune in north-central France, located in the western outskirts of Paris within the Yvelines department.
  • E. Arras
    Arras is a historic city in northern France renowned for its Flemish-Baroque architecture, grand squares, and role as a strategic site in both World Wars.
  • 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_69bd43daa3e4819090b59d127db70e57 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd86588af081908c846fcde65724da completed March 20, 2026, 5:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf7fd0a2c48190ba0c2e3259c3691f completed March 22, 2026, 5:36 a.m.
Created at: March 20, 2026, 2:02 p.m.