Triple

T441107
Position Surface form Disambiguated ID Type / Status
Subject Bangalore English E10114 entity
Predicate typicalSpeakers P3327 FINISHED
Object young professionals in Bengaluru 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: young professionals in Bengaluru | Statement: [Bangalore English, typicalSpeakers, young professionals in Bengaluru]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: typicalSpeakers
Context triple: [Bangalore English, typicalSpeakers, young professionals in Bengaluru]
  • A. typicalSpeaker chosen
    Indicates that the subject is a prototypical or characteristic speaker or source of utterances in the context of the object.
  • B. religionAssociatedWithSpeakers
    Indicates a relationship where a particular religion is associated with, practiced by, or identified as belonging to specific speakers.
  • C. spokeAt
    Indicates that a person delivered a talk, speech, or presentation at a particular event or location.
  • D. typicalCandidate
    Indicates that an entity is a standard or representative example of what is usually considered a candidate in a given context.
  • E. hasOfficialSpokespersons
    Indicates that an entity is formally represented or spoken for by one or more designated spokespersons in an official capacity.
  • 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_69a2e8465ef481909655c681b01e2986 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2ef2af84881909635ebbbb3465b1b completed Feb. 28, 2026, 1:35 p.m.
PD Predicate disambiguation batch_69a2eddcf50c8190bfa0d1f8ee9f604a completed Feb. 28, 2026, 1:30 p.m.
Created at: Feb. 28, 2026, 1:11 p.m.