Triple

T1387146
Position Surface form Disambiguated ID Type / Status
Subject Saône-et-Loire E29871 entity
Predicate containsAdministrativeTerritorialEntity P747 FINISHED
Object Le Creusot
Le Creusot is an industrial town in eastern France historically known for its steelworks and heavy engineering industries.
E160692 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: Le Creusot | Statement: [Saône-et-Loire, containsAdministrativeTerritorialEntity, Le Creusot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Le Creusot
Context triple: [Saône-et-Loire, containsAdministrativeTerritorialEntity, Le Creusot]
  • A. Herstal
    Herstal is an industrial town in the Liège province of eastern Belgium, known historically for its arms manufacturing and proximity to the city of Liège.
  • B. Eiffel et Cie
    Eiffel et Cie was the engineering and construction firm through which Gustave Eiffel carried out many of his major iron-structure projects in the late 19th century.
  • C. Traton
    Traton is a commercial vehicle manufacturer and holding company that oversees brands like MAN and Scania within the Volkswagen Group.
  • D. Borsigwerke
    Borsigwerke is a Berlin U-Bahn station on line U6 serving the Tegel district in the city’s northwest.
  • E. Union Steel
    Union Steel was an American steel company historically associated with industrialist and financier Andrew W. Mellon.
  • 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: Le Creusot
Triple: [Saône-et-Loire, containsAdministrativeTerritorialEntity, Le Creusot]
Generated description
Le Creusot is an industrial town in eastern France historically known for its steelworks and heavy engineering industries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Le Creusot
Target entity description: Le Creusot is an industrial town in eastern France historically known for its steelworks and heavy engineering industries.
  • A. Herstal
    Herstal is an industrial town in the Liège province of eastern Belgium, known historically for its arms manufacturing and proximity to the city of Liège.
  • B. Eiffel et Cie
    Eiffel et Cie was the engineering and construction firm through which Gustave Eiffel carried out many of his major iron-structure projects in the late 19th century.
  • C. Traton
    Traton is a commercial vehicle manufacturer and holding company that oversees brands like MAN and Scania within the Volkswagen Group.
  • D. Borsigwerke
    Borsigwerke is a Berlin U-Bahn station on line U6 serving the Tegel district in the city’s northwest.
  • E. Union Steel
    Union Steel was an American steel company historically associated with industrialist and financier Andrew W. Mellon.
  • 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_69a498dc92f8819094a1108f8ac90f43 completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c33b6e108190b6b2bca4ddd97b6c completed March 1, 2026, 10:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69acde1f08e08190871fd9d539e902c8 completed March 8, 2026, 2:25 a.m.
NEDg Description generation batch_69acdf4e74b08190a18df73cca054b28 completed March 8, 2026, 2:30 a.m.
NED2 Entity disambiguation (via description) batch_69ace03eabf48190a79b5112fb2a917d completed March 8, 2026, 2:34 a.m.
Created at: March 1, 2026, 7:59 p.m.