Triple

T30161233
Position Surface form Disambiguated ID Type / Status
Subject Victoria (central area) E766671 entity
Predicate hasOfficeDevelopment P177347 FINISHED
Object Nova Victoria
Nova Victoria is a major mixed-use office and retail development in central London’s Victoria district, known for its contemporary architecture and proximity to Victoria Station.
 E1900510 NE FINISHED

How this triple was built (3 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: Nova Victoria | Statement: [Victoria (central area), hasOfficeDevelopment, Nova Victoria]
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: Nova Victoria
Triple: [Victoria (central area), hasOfficeDevelopment, Nova Victoria]
Generated description
Nova Victoria is a major mixed-use office and retail development in central London’s Victoria district, known for its contemporary architecture and proximity to Victoria Station.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: hasOfficeDevelopment
Context triple: [Victoria (central area), hasOfficeDevelopment, Nova Victoria]
  • A. hasOffice
    Indicates that an entity possesses or maintains an office at a particular location or within a specific organization.
  • B. hasOfficeType
    Indicates that an entity’s office is classified as a specific type or category of office.
  • C. hasDevelopmentOrganization
    Indicates that an entity is associated with, managed by, or supported by a specific organization responsible for its development.
  • D. hasOfficeCluster
    Indicates that an entity is associated with or belongs to a specific group or cluster of office locations.
  • E. hasOfficeBuildings
    Indicates that one entity possesses, controls, or is associated with one or more office buildings.
  • F. None of above. chosen

Provenance (7 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_69f2247a968881909d79c18f2bfcb275 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6fb93224881908fc66fe76115fcdb completed May 3, 2026, 7:38 a.m.
NED1 Entity disambiguation (via context triple) batch_6a274cc73eb481909555e2886d37751d completed June 8, 2026, 11:14 p.m.
NEDg Description generation batch_6a274d5a67ec81909f2e7f0b7a91a280 completed June 8, 2026, 11:16 p.m.
NED2 Entity disambiguation (via description) batch_6a274dbbc3e481909601c15e6843fe92 completed June 8, 2026, 11:18 p.m.
PD Predicate disambiguation batch_69f6f969b4cc8190afb473a2d8b110bc completed May 3, 2026, 7:29 a.m.
PDg Predicate description generation batch_69f6fb17d5ec81909091e37e1ddbe577 completed May 3, 2026, 7:36 a.m.
Created at: April 29, 2026, 7:21 p.m.