Triple

T21746118
Position Surface form Disambiguated ID Type / Status
Subject Trichardt E536791 entity
Predicate nearbyIndustrialHub P20649 FINISHED
Object Secunda NE NERFINISHED

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: Secunda | Statement: [Trichardt, nearbyIndustrialHub, Secunda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Secunda
Context triple: [Trichardt, nearbyIndustrialHub, Secunda]
  • A. Secunda chosen
    Secunda is a South African industrial town in Mpumalanga province, best known for its large coal-to-liquid fuel and petrochemical operations centered around Sasol’s facilities.
  • B. Secunda
    Secunda is a surname most notably associated with Sholem Secunda, a prominent 20th-century American composer of Yiddish and popular music.
  • C. Moura
    Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
  • D. Moura
    Moura is a small coal-mining town in Central Queensland, Australia, known for its agricultural activities and history of mining disasters.
  • E. Moura
    Moura is a Portuguese-language surname commonly found in Brazil and other Lusophone countries, associated with various notable figures in arts, sports, and public life.
  • 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: nearbyIndustrialHub
Context triple: [Trichardt, nearbyIndustrialHub, Secunda]
  • A. hasNearbyIndustry chosen
    Indicates that an entity is located close to one or more industrial facilities or activities.
  • B. nearbyEconomicActivity
    Indicates that there is economic activity occurring in close physical proximity to the referenced entity.
  • C. infrastructureNearby
    Indicates that one entity is located close to another entity that serves as infrastructure (such as roads, utilities, or public facilities).
  • D. nearbyUrbanCenter
    Indicates that one location is geographically close to an urban center, such as a city or large town.
  • E. connectsToIndustrialArea
    Indicates that one entity has a direct link, route, or access connection to an industrial area.
  • 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_69e0c46df5448190b4322127ffc4c690 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f01a76540c8190b91a67f4a70869fb completed April 28, 2026, 2:24 a.m.
PD Predicate disambiguation batch_69e6969c16fc8190b5126c169317d85d completed April 20, 2026, 9:11 p.m.
Created at: April 16, 2026, 6:49 p.m.