Triple

T3794362
Position Surface form Disambiguated ID Type / Status
Subject Agere Systems E89731 entity
Predicate hadManufacturingFacility P25392 FINISHED
Object Orlando, Florida E11265 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: Orlando, Florida | Statement: [Agere Systems, hadManufacturingFacility, Orlando, Florida]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orlando, Florida
Context triple: [Agere Systems, hadManufacturingFacility, Orlando, Florida]
  • A. Orlando chosen
    Orlando is a major city in central Florida known for its theme parks, tourism industry, and entertainment attractions.
  • B. Orlando
    Orlando is a 1992 British period fantasy film, based on Virginia Woolf’s novel, in which Tilda Swinton plays an androgynous noble who lives for centuries while changing gender.
  • C. Orlando
    Orlando is a historic township area within Soweto, South Africa, known for its central role in the anti-apartheid struggle and vibrant local culture.
  • D. Orlando
    Orlando is a common Italian surname borne by numerous individuals, including notable political and cultural figures.
  • E. Kissimmee, Florida
    Kissimmee, Florida is a central Florida city in Osceola County known for its proximity to major Orlando-area theme parks and tourist attractions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hadManufacturingFacility
Context triple: [Agere Systems, hadManufacturingFacility, Orlando, Florida]
  • A. hasIndustrialPlant chosen
    Indicates that an entity possesses, operates, or is associated with an industrial plant facility.
  • B. mainManufacturingSite
    Indicates the primary location where an entity’s products are manufactured or produced.
  • C. hasIndustrialCompany
    Indicates that one entity possesses, controls, or is associated with an industrial company.
  • D. hasProduction
    Indicates that an entity is associated with, or responsible for, the creation or manufacture of another entity or product.
  • E. hasMajorProductionSystem
    Indicates that an entity primarily operates, utilizes, or is characterized by a particular major production system.
  • F. None of above.

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_69aed9597d6881909b6ee3b9de859223 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeecefa3608190a7a20ed6df6a64b2 completed March 9, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5560d5ad4819086d7c34e53afb4f6 completed March 14, 2026, 12:35 p.m.
PD Predicate disambiguation batch_69aee743c8d08190a9f9c97b836bd703 completed March 9, 2026, 3:29 p.m.
Created at: March 9, 2026, 3:15 p.m.