Triple

T8815845
Position Surface form Disambiguated ID Type / Status
Subject Noordermarkt E209774 entity
Predicate cityDistrict P2709 FINISHED
Object Centrum
Centrum is the historic city center district of Amsterdam, known for its canals, landmarks, and bustling markets.
 E758649 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: Centrum | Statement: [Noordermarkt, cityDistrict, Centrum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Centrum
Context triple: [Noordermarkt, cityDistrict, Centrum]
  • A. Centrum
    Centrum is the central urban district and main commercial area of the Dutch city of Meppel.
  • B. Centrum
    Centrum is the central district and main urban core of the Dutch municipality of Ridderkerk.
  • C. Innenstadt
    Innenstadt is the central urban district of Frankfurt am Main, known as the city’s historic core and primary commercial area.
  • D. Centrs
    Centrs is the central district of Riga, Latvia, known for its historic architecture, cultural institutions, and commercial activity.
  • E. Centrale
    Centrale is a major shopping centre located in the London Borough of Croydon, featuring a wide range of retail stores and services.
  • 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: Centrum
Triple: [Noordermarkt, cityDistrict, Centrum]
Generated description
Centrum is the historic city center district of Amsterdam, known for its canals, landmarks, and bustling markets.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Centrum
Target entity description: Centrum is the historic city center district of Amsterdam, known for its canals, landmarks, and bustling markets.
  • A. Centrum
    Centrum is the central urban district and main commercial area of the Dutch city of Meppel.
  • B. Centrum
    Centrum is the central district and main urban core of the Dutch municipality of Ridderkerk.
  • C. Innenstadt
    Innenstadt is the central urban district of Frankfurt am Main, known as the city’s historic core and primary commercial area.
  • D. Centrs
    Centrs is the central district of Riga, Latvia, known for its historic architecture, cultural institutions, and commercial activity.
  • E. Centrale
    Centrale is a prestigious French engineering school renowned for its rigorous scientific curriculum and role in training elite engineers and industry leaders.
  • 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_69ca8364e13081909c85fe80f44fe86f completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5ff2ff248190bafcafe8b3860e53 completed March 31, 2026, 11:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf6fb898388190b96242ff41599250 completed April 3, 2026, 7:43 a.m.
NEDg Description generation batch_69cf7101b0088190843affad2474eb32 completed April 3, 2026, 7:49 a.m.
NED2 Entity disambiguation (via description) batch_69cf725ebb4c8190be3b19e9c5e854ac completed April 3, 2026, 7:55 a.m.
Created at: March 30, 2026, 6:45 p.m.