Triple

T2897343
Position Surface form Disambiguated ID Type / Status
Subject City of Bruges E63971 entity
Predicate river P165 FINISHED
Object Reie
Reie is a historic canalized river in Bruges, Belgium, that forms part of the city’s iconic medieval waterways.
 E307704 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: Reie | Statement: [City of Bruges, river, Reie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Reie
Context triple: [City of Bruges, river, Reie]
  • A. Rittō
    Rittō is a city in Shiga Prefecture, Japan, known for its residential communities and proximity to the Kyoto–Osaka metropolitan area.
  • B. Yukio
    Yukio is a Japanese given name commonly used for males and borne by several notable figures in politics, arts, and entertainment.
  • C. Rie
    Rie is a common diminutive or nickname form of the given name Marie, used in various European languages.
  • D. Chō
    Chō is a Japanese surname borne by various notable individuals across fields such as the military, arts, and entertainment.
  • E. Yasu
    Yasu is a Japanese city located in Shiga Prefecture, known for its blend of residential areas, local industry, and proximity to Lake Biwa.
  • 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: Reie
Triple: [City of Bruges, river, Reie]
Generated description
Reie is a historic canalized river in Bruges, Belgium, that forms part of the city’s iconic medieval waterways.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Reie
Target entity description: Reie is a historic canalized river in Bruges, Belgium, that forms part of the city’s iconic medieval waterways.
  • A. Rittō
    Rittō is a city in Shiga Prefecture, Japan, known for its residential communities and proximity to the Kyoto–Osaka metropolitan area.
  • B. Yukio
    Yukio is a Japanese given name commonly used for males and borne by several notable figures in politics, arts, and entertainment.
  • C. Rie
    Rie is a common diminutive or nickname form of the given name Marie, used in various European languages.
  • D. Chō
    Chō is a Japanese surname borne by various notable individuals across fields such as the military, arts, and entertainment.
  • E. Yasu
    Yasu is a Japanese city located in Shiga Prefecture, known for its blend of residential areas, local industry, and proximity to Lake Biwa.
  • 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_69ab4c45822c8190830c5f2bb97bcfd0 completed March 6, 2026, 9:51 p.m.
NER Named-entity recognition batch_69abe08e7b248190a6bb0f6999f99c23 completed March 7, 2026, 8:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69b03188d84081909e23b46c2f75250b completed March 10, 2026, 2:58 p.m.
NEDg Description generation batch_69b036ef40188190880dfe3592107b0e completed March 10, 2026, 3:21 p.m.
NED2 Entity disambiguation (via description) batch_69b03bca591c81908b3734cc8f2e712b completed March 10, 2026, 3:42 p.m.
Created at: March 6, 2026, 10:08 p.m.