Triple

T2129403
Position Surface form Disambiguated ID Type / Status
Subject A4 motorway (France) E46501 entity
Predicate passesNear P416 FINISHED
Object Saint-Dizier
Saint-Dizier is a commune in northeastern France known as an industrial town in the Haute-Marne department of the Grand Est region.
 E335494 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: Saint-Dizier | Statement: [A4 motorway (France), passesNear, Saint-Dizier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Saint-Dizier
Context triple: [A4 motorway (France), passesNear, Saint-Dizier]
  • A. Tournus
    Tournus is a historic town in eastern France’s Burgundy region, known for its Romanesque abbey and riverside setting along the Saône.
  • B. Bourges
    Bourges is a historic city in central France known for its well-preserved medieval architecture and its UNESCO-listed Gothic cathedral, Saint-Étienne.
  • C. Vierzon
    Vierzon is a town in central France known historically as an industrial and railway hub in the Cher department of the Centre-Val de Loire region.
  • D. Melun
    Melun is a historic commune in the Île-de-France region of north-central France, known as a regional administrative center and former royal town southeast of Paris.
  • E. Mâcon
    Mâcon is a historic town in eastern France’s Burgundy region, known for its wine production and picturesque setting along the Saône River.
  • 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: Saint-Dizier
Triple: [A4 motorway (France), passesNear, Saint-Dizier]
Generated description
Saint-Dizier is a commune in northeastern France known as an industrial town in the Haute-Marne department of the Grand Est region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Saint-Dizier
Target entity description: Saint-Dizier is a commune in northeastern France known as an industrial town in the Haute-Marne department of the Grand Est region.
  • A. Tournus
    Tournus is a historic town in eastern France’s Burgundy region, known for its Romanesque abbey and riverside setting along the Saône.
  • B. Bourges
    Bourges is a historic city in central France known for its well-preserved medieval architecture and its UNESCO-listed Gothic cathedral, Saint-Étienne.
  • C. Vierzon
    Vierzon is a town in central France known historically as an industrial and railway hub in the Cher department of the Centre-Val de Loire region.
  • D. Melun
    Melun is a historic commune in the Île-de-France region of north-central France, known as a regional administrative center and former royal town southeast of Paris.
  • E. Mâcon
    Mâcon is a historic town in eastern France’s Burgundy region, known for its wine production and picturesque setting along the Saône River.
  • 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_69a88a1626548190ae59a5028c3baa8e completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbb77ccc4819087bee5dbb91b5ae8 completed March 7, 2026, 5:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69b24a9a49e481908f1916cbff31d908 completed March 12, 2026, 5:09 a.m.
NEDg Description generation batch_69b24c5154008190aaaf07333de85370 completed March 12, 2026, 5:17 a.m.
NED2 Entity disambiguation (via description) batch_69b24cf888288190b02782467c932862 completed March 12, 2026, 5:19 a.m.
Created at: March 4, 2026, 7:44 p.m.