Triple

T3864199
Position Surface form Disambiguated ID Type / Status
Subject Bishopric of Thérouanne E91810 entity
Predicate locatedIn P40 FINISHED
Object Thérouanne
Thérouanne is a historic town in northern France that once served as an important medieval religious center and episcopal seat.
 E395464 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: Thérouanne | Statement: [Bishopric of Thérouanne, locatedIn, Thérouanne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Thérouanne
Context triple: [Bishopric of Thérouanne, locatedIn, Thérouanne]
  • A. 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.
  • B. Cambrai
    Cambrai is a historic city in northern France known for its medieval heritage, role in World War I, and traditional confectionery.
  • C. Péronne
    Péronne is a historic town in northern France known for its role in World War I and its location in the Somme department.
  • D. Creil
    Creil is a commuter town in northern France’s Oise department, known as a regional rail hub connecting Paris with Picardy via major train and RER lines.
  • E. 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.
  • 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: Thérouanne
Triple: [Bishopric of Thérouanne, locatedIn, Thérouanne]
Generated description
Thérouanne is a historic town in northern France that once served as an important medieval religious center and episcopal seat.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Thérouanne
Target entity description: Thérouanne is a historic town in northern France that once served as an important medieval religious center and episcopal seat.
  • A. 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.
  • B. Cambrai
    Cambrai is a historic city in northern France known for its medieval heritage, role in World War I, and traditional confectionery.
  • C. Péronne
    Péronne is a historic town in northern France known for its role in World War I and its location in the Somme department.
  • D. Creil
    Creil is a commuter town in northern France’s Oise department, known as a regional rail hub connecting Paris with Picardy via major train and RER lines.
  • E. 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.
  • 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_69aed9645f348190a9868e7cef56ab7e completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeec3871d881909c6c8e6d08203801 completed March 9, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5123ad9188190a158721a6192cdae completed March 14, 2026, 7:46 a.m.
NEDg Description generation batch_69b51336c5f8819096b0b6cee47e48e3 completed March 14, 2026, 7:50 a.m.
NED2 Entity disambiguation (via description) batch_69b513b11dcc8190a2c2e3f27b4cf25e completed March 14, 2026, 7:52 a.m.
Created at: March 9, 2026, 3:19 p.m.