Triple

T37084637
Position Surface form Disambiguated ID Type / Status
Subject Rue Neuve E918248 entity
Predicate hasShoppingMallsNearby P16039 FINISHED
Object City2 shopping center
City2 shopping center is a major retail complex located on Brussels’ busy Rue Neuve, featuring a wide range of shops, dining options, and services.
 E2213019 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: City2 shopping center | Statement: [Rue Neuve, hasShoppingMallsNearby, City2 shopping center]
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: City2 shopping center
Triple: [Rue Neuve, hasShoppingMallsNearby, City2 shopping center]
Generated description
City2 shopping center is a major retail complex located on Brussels’ busy Rue Neuve, featuring a wide range of shops, dining options, and services.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: hasShoppingMallsNearby
Context triple: [Rue Neuve, hasShoppingMallsNearby, City2 shopping center]
  • A. hasShoppingMall chosen
    Indicates that one entity possesses, contains, or includes a shopping mall within its area or domain.
  • B. hasShoppingDistrict
    Indicates that a place contains or is associated with a designated area where multiple shops and commercial retail activities are concentrated.
  • C. hasShoppingDistrictType
    Indicates that an entity is associated with a particular type or category of shopping district.
  • D. hasConvenienceStore
    Indicates that one entity possesses, contains, or is associated with a convenience store.
  • E. hasShoppingDistrictName
    Indicates that an entity’s shopping district is identified by a specific name.
  • F. None of above.

Provenance (6 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_69f76e9952b88190a6fe01ba01476520 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fcc4b700748190ae00b21d09c96695 completed May 7, 2026, 4:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3efdc87fa08190b25f7ab8a395c100 completed June 26, 2026, 10:31 p.m.
NEDg Description generation batch_6a3f444ba9ec8190bb6ad6b98d2f19f9 completed June 27, 2026, 3:32 a.m.
NED2 Entity disambiguation (via description) batch_6a3f453d286481909c3f05d6af7dfeb7 completed June 27, 2026, 3:36 a.m.
PD Predicate disambiguation batch_69fcb0f9d3d881908a049475182fb039 completed May 7, 2026, 3:34 p.m.
Created at: May 3, 2026, 4:14 p.m.