Triple

T15043199
Position Surface form Disambiguated ID Type / Status
Subject Allenby Street (Tel Aviv) E379153 entity
Predicate hasSectionCharacterizedBy P85325 FINISHED
Object dense retail frontage 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: dense retail frontage | Statement: [Allenby Street (Tel Aviv), hasSectionCharacterizedBy, dense retail frontage]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasSectionCharacterizedBy
Context triple: [Allenby Street (Tel Aviv), hasSectionCharacterizedBy, dense retail frontage]
  • A. hasSectionRole
    Indicates that an entity holds a specific role or function within a particular section or subdivision of a larger structure or context.
  • B. hasSectionOn
    Indicates that one entity (typically a document or resource) contains a dedicated section or part that specifically addresses or discusses another entity or topic.
  • C. hasSectionIn
    Indicates that one entity contains or includes another entity as a section or subdivision within it.
  • D. hasSectionWith chosen
    Indicates that an entity contains or includes a specific section that satisfies certain conditions or characteristics.
  • E. hasSect
    Indicates that an entity includes, contains, or is associated with a particular sect or subgroup within a larger religious, ideological, or organizational context.
  • F. None of above.

Provenance (3 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_69d85cd64d108190853797a95c11cc45 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded82f73208190bb55fa6b20074e27 completed April 15, 2026, 12:13 a.m.
PD Predicate disambiguation batch_69de9a69d7848190b2b4662dd30f20e9 completed April 14, 2026, 7:50 p.m.
Created at: April 10, 2026, 3 a.m.