Triple

T1451610
Position Surface form Disambiguated ID Type / Status
Subject Robert Cailliau E31302 entity
Predicate placeOfBirth P1 FINISHED
Object Tongeren
Tongeren is a historic city in eastern Belgium, known as the country’s oldest town and for its well-preserved Roman and medieval heritage.
 E238388 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: Tongeren | Statement: [Robert Cailliau, placeOfBirth, Tongeren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tongeren
Context triple: [Robert Cailliau, placeOfBirth, Tongeren]
  • A. Betuwe
    Betuwe is a fertile riverine region in the Dutch province of Gelderland, renowned for its extensive fruit orchards and scenic landscapes between the Rhine and Waal rivers.
  • B. Uithoorn
    Uithoorn is a town and municipality in the province of North Holland in the Netherlands, situated along the Amstel River.
  • C. Nieuwenhoorn
    Nieuwenhoorn is a village in the western Netherlands that forms part of the province of South Holland.
  • D. Biezelinge
    Biezelinge is a small village in the Dutch province of Zeeland, known as the birthplace of former Prime Minister Jan Peter Balkenende.
  • E. Teylingen
    Teylingen is a municipality in the Dutch province of South Holland, known for its historic estates and proximity to the bulb-growing region.
  • 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: Tongeren
Triple: [Robert Cailliau, placeOfBirth, Tongeren]
Generated description
Tongeren is a historic city in eastern Belgium, known as the country’s oldest town and for its well-preserved Roman and medieval heritage.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tongeren
Target entity description: Tongeren is a historic city in eastern Belgium, known as the country’s oldest town and for its well-preserved Roman and medieval heritage.
  • A. Betuwe
    Betuwe is a fertile riverine region in the Dutch province of Gelderland, renowned for its extensive fruit orchards and scenic landscapes between the Rhine and Waal rivers.
  • B. Uithoorn
    Uithoorn is a town and municipality in the province of North Holland in the Netherlands, situated along the Amstel River.
  • C. Nieuwenhoorn
    Nieuwenhoorn is a village in the western Netherlands that forms part of the province of South Holland.
  • D. Biezelinge
    Biezelinge is a small village in the Dutch province of Zeeland, known as the birthplace of former Prime Minister Jan Peter Balkenende.
  • E. Teylingen
    Teylingen is a municipality in the Dutch province of South Holland, known for its historic estates and proximity to the bulb-growing region.
  • 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_69a499171a28819085b993a3ac78e363 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c57bc0908190a57e6bc3d20d5e3c completed March 1, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae58a7b1fc8190b76b09e64097b881 completed March 9, 2026, 5:20 a.m.
NEDg Description generation batch_69ae597198b88190b0253aa121ed35e1 completed March 9, 2026, 5:24 a.m.
NED2 Entity disambiguation (via description) batch_69ae59ff1234819083bbfdce270cb584 completed March 9, 2026, 5:26 a.m.
Created at: March 1, 2026, 8 p.m.