Triple

T37235450
Position Surface form Disambiguated ID Type / Status
Subject BayArena E923559 entity
Predicate nearbyCompany P82033 FINISHED
Object Bayer AG headquarters 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: Bayer AG headquarters | Statement: [BayArena, nearbyCompany, Bayer AG headquarters]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: nearbyCompany
Context triple: [BayArena, nearbyCompany, Bayer AG headquarters]
  • A. nearbyEconomicActivity
    Indicates that there is economic activity occurring in close physical proximity to the referenced entity.
  • B. hasMajorCompanyNearby chosen
    Indicates that a location or entity is situated close to at least one large or significant company.
  • C. sectorCapitalNearby
    Indicates that the capital city of a given sector is geographically close to another specified location or entity.
  • D. operatesNear
    Indicates that one entity performs its activities or functions in close physical proximity to another entity.
  • E. nearbyUse
    Indicates that one entity uses or operates another entity that is located nearby or in close physical proximity.
  • 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_69f76ea9fee88190a589f661d95a7189 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69ff136ed2a881908f713401083970d1 completed May 9, 2026, 10:58 a.m.
PD Predicate disambiguation batch_69ff10f9e3448190b6cb6ea5a67713c1 completed May 9, 2026, 10:48 a.m.
Created at: May 3, 2026, 4:15 p.m.