Triple

T33290609
Position Surface form Disambiguated ID Type / Status
Subject Europa Passage E852308 entity
Predicate hasShopCount P181092 FINISHED
Object about 120 LITERAL FINISHED

How this triple was built (2 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: about 120 | Statement: [Europa Passage, hasShopCount, about 120]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasShopCount
Context triple: [Europa Passage, hasShopCount, about 120]
  • A. hasShop
    Indicates that one entity owns, operates, or is associated with a shop or retail establishment.
  • B. hasShopsOn
    Indicates that one entity (typically a street, area, or building) contains or is lined with shops located on or along it.
  • C. hasIndependentShops
    Indicates that an entity contains or is associated with retail businesses that operate independently rather than as part of large chains or franchises.
  • D. hasShopsOfType
    Indicates that an entity contains or is associated with one or more shops belonging to a specified type or category.
  • E. hasOnlineShop
    Indicates that an entity operates or is associated with a shop that sells goods or services via the internet.
  • F. None of above. chosen

Provenance (4 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_69f349660ff48190a4568803d0b89941 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f760a35b988190904e6267553ad2fe completed May 3, 2026, 2:50 p.m.
PD Predicate disambiguation batch_69f75eb3d6f081908c933474eb359e3d completed May 3, 2026, 2:41 p.m.
PDg Predicate description generation batch_69f760a2a90c8190b8fbc55412ab752b completed May 3, 2026, 2:50 p.m.
Created at: May 1, 2026, 1:32 a.m.